Cellula Robotics Partners With The NOC To Advance – Marine Technology News

The U.K. National Oceanography Centers (NOC) Marine Robotics Innovation Center announced that Cellula Robotics is joining its thriving community of partners.

Cellula Robotics Ltd. is a privately-owned company founded and based in Vancouver, B.C., since 2001. The firm currently has a team of around 30 engineers, technicians and program managers based in its combined office and workshop facilities in Burnaby, on the outskirts of Vancouver. It also has a regional office in Aberdeenshire, U.K., which currently concentrates on business development, customer support and project management.

Cellula is engaged in three main commercial product development programs, autonomous underwater vehicle (AUV) systems, subsea geotechnical systems and bespoke subsea robotics systems engineering and control system products. Cellula have clients across the globe in offshore defense, oil and gas, ocean exploration and renewables markets.

Cellula Robotics have worked with the NOC previously, supplying a bespoke subsea drilling rig in 2019 for the high profile STEMM-CCS project which successfully demonstrated the potential of innovative new techniques for Carbon Capture and Storage in the marine environment.

The NOC is the U.K.s hub for the development of marine autonomous and robotic systems, and this new partnership will further enable Cellula Robotics to collaborate and share expertise with the Centers other strategic partners in the advancement of cutting-edge marine autonomous technology.

Aidan Thorn, Innovation Center manager, said, Its great to have Cellula Robotics join the Marine Robotics Innovation Centre. Our interactions in getting to this point have shown that they have a truly collaborative approach to what they do, making them an ideal partner to engage with the community. There are a number of very obvious synergies between Cellulas work and the NOCs own work on marine autonomous systems, and this agreement enables us to explore how we can work together going forward.

Allan Spencer, Managing Director, Cellula Robotics UK Ltd., said, We are delighted to be joining the Innovation Center. Many of our successfully developed products and systems have been the result of open collaboration with other system developers and suppliers. We ourselves have also often provided complete subsystems, engineering and project management services to other system integrators and builders, so we would consider representation by Cellula Robotics in the NOC community and network mutually advantageous, and we very much look forward to exploring this bilateral relationship further over the coming year.

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Cellula Robotics Partners With The NOC To Advance - Marine Technology News

World With nearly 4 million industrial robots by 2022, demand will rise for workers with robotics skills – Staffing Industry Analysts

06 August 2020

The International Federation of Robotics says there will be almost 4 million industrial robots in factories worldwide by 2022. And while that will drive demand for workers skilled in robots, countries must update their educational systems.

Governments and companies around the globe now need to focus on providing the right skills necessary to work with robots and intelligent automation systems, said Milton Guerry, president of the International Federation of Robotics.

This is important to take maximum advantage of the opportunities that these technologies offer, Guerry continued. The post-corona recovery will further accelerate the deployment of robotics. Policies and strategies are important to help workforces make the transition to a more automated economy.

The organisation cited research by The Economist Intelligence Unit that only four countries have already established mature education policies to deal with the challenges of an automated economy. South Korea was the leader, followed by Estonia, Singapore and Germany.

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World With nearly 4 million industrial robots by 2022, demand will rise for workers with robotics skills - Staffing Industry Analysts

Collaborative Robots Market Research Report by Component, by Payload Capacity, by Function, by Application, by Industry – Global Forecast to 2025 -…

New York, Aug. 06, 2020 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Collaborative Robots Market Research Report by Component, by Payload Capacity, by Function, by Application, by Industry - Global Forecast to 2025 - Cumulative Impact of COVID-19" - https://www.reportlinker.com/p05913886/?utm_source=GNW

The Global Collaborative Robots Market is expected to grow from USD 216.55 Million in 2019 to USD 1,438.93 Million by the end of 2025 at a Compound Annual Growth Rate (CAGR) of 37.11%.

Market Segmentation & Coverage:This research report categorizes the Collaborative Robots to forecast the revenues and analyze the trends in each of the following sub-markets:

Based on Component , the Collaborative Robots Market studied across Hardware and Software. The Hardware further studied across Controller, Drive, End Effector, and Sensor.

Based on Payload Capacity, the Collaborative Robots Market studied across Above 10kg, Between 5 and 10kg, and Up to 5 Kg.

Based on Function, the Collaborative Robots Market studied across Hand Guiding, Power and Force Limiting, Safety-Rated Monitored Stop, and Speed Reduction and Separation Monitoring.

Based on Application, the Collaborative Robots Market studied across Assembly, Gluing and Welding, Machine Tending, Material Handling, Packaging and Palletizing, Pick and Place, and Quality Testing.

Based on Industry, the Collaborative Robots Market studied across Automotive, Electronics, Food & Beverages, Furniture and Equipment, Healthcare, Metals and Machining, and Plastics and Polymers.

Based on Geography, the Collaborative Robots Market studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas region surveyed across Argentina, Brazil, Canada, Mexico, and United States. The Asia-Pacific region surveyed across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, South Korea, and Thailand. The Europe, Middle East & Africa region surveyed across France, Germany, Italy, Netherlands, Qatar, Russia, Saudi Arabia, South Africa, Spain, United Arab Emirates, and United Kingdom.

Company Usability Profiles:The report deeply explores the recent significant developments by the leading vendors and innovation profiles in the Global Collaborative Robots Market including ABB, Aubo Robotics Inc., Comau S.P.A, Energid Technologies Corporation, F&P Robotics AG, Fanuc Corporation, Franka Emika GmbH, Kawada Robotics Corp., Kuka AG, Mabi Ag, Mrk-Systeme GmbH, Precise Automation, Inc., Rethink Robotics, Robert Bosch GmbH, Techman Robot for Quanta Storage Inc., Universal Robots A/S, and Yaskawa Electric Corporation.

FPNV Positioning Matrix:The FPNV Positioning Matrix evaluates and categorizes the vendors in the Collaborative Robots Market on the basis of Business Strategy (Business Growth, Industry Coverage, Financial Viability, and Channel Support) and Product Satisfaction (Value for Money, Ease of Use, Product Features, and Customer Support) that aids businesses in better decision making and understanding the competitive landscape.

Competitive Strategic Window:The Competitive Strategic Window analyses the competitive landscape in terms of markets, applications, and geographies. The Competitive Strategic Window helps the vendor define an alignment or fit between their capabilities and opportunities for future growth prospects. During a forecast period, it defines the optimal or favorable fit for the vendors to adopt successive merger and acquisition strategies, geography expansion, research & development, and new product introduction strategies to execute further business expansion and growth.

Cumulative Impact of COVID-19:COVID-19 is an incomparable global public health emergency that has affected almost every industry, so for and, the long-term effects projected to impact the industry growth during the forecast period. Our ongoing research amplifies our research framework to ensure the inclusion of underlaying COVID-19 issues and potential paths forward. The report is delivering insights on COVID-19 considering the changes in consumer behavior and demand, purchasing patterns, re-routing of the supply chain, dynamics of current market forces, and the significant interventions of governments. The updated study provides insights, analysis, estimations, and forecast, considering the COVID-19 impact on the market.

The report provides insights on the following pointers:1. Market Penetration: Provides comprehensive information on the market offered by the key players2. Market Development: Provides in-depth information about lucrative emerging markets and analyzes the markets3. Market Diversification: Provides detailed information about new product launches, untapped geographies, recent developments, and investments4. Competitive Assessment & Intelligence: Provides an exhaustive assessment of market shares, strategies, products, and manufacturing capabilities of the leading players5. Product Development & Innovation: Provides intelligent insights on future technologies, R&D activities, and new product developments

The report answers questions such as:1. What is the market size and forecast of the Global Collaborative Robots Market?2. What are the inhibiting factors and impact of COVID-19 shaping the Global Collaborative Robots Market during the forecast period?3. Which are the products/segments/applications/areas to invest in over the forecast period in the Global Collaborative Robots Market?4. What is the competitive strategic window for opportunities in the Global Collaborative Robots Market?5. What are the technology trends and regulatory frameworks in the Global Collaborative Robots Market?6. What are the modes and strategic moves considered suitable for entering the Global Collaborative Robots Market?Read the full report: https://www.reportlinker.com/p05913886/?utm_source=GNW

About ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

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Collaborative Robots Market Research Report by Component, by Payload Capacity, by Function, by Application, by Industry - Global Forecast to 2025 -...

Apex in-game teaser sprays an R over Hammond Robotics signs in World’s Edge – Dot Esports

Hammond Robotics cant catch a break. Apex Legends latest teaser sprayed over the companys future worksites signs with a mysterious symbol, an R that could be a hint to the games next possible legend.

The signs were part of the first teaser for season six and anticipated that Hammond Robotics still had its sights on Worlds Edgepossibly even hinting at a map update. The latest teaser painted over the signs with a new symbol: a capital R circumscribed onto a semicircle with five dots on top. The community speculates that it could be a reference to a possible data-mined legend called Rampart.

Data miners pointed out that Rampart could be the next legend due to the sheer amount of her assets being added to the game files, including animation names, sprays, and possibly character art. Shrugtal, a prominent figure in the Apex community, compiled key bits of information about the legend in a video.

The mysterious R symbol has officially appeared in Apex before. Ramparts possible trademark is visible on reactive skins for both the Flatline and the Wingman, which could suggest that the legend is behind some of the weapon designs. Data-mined information points out that Rampart could be a gunsmith of sorts, and the shop R might be their way of promoting the business.

The R symbol seen on the signs also appears in the data-mined paintball hop-up, which will reportedly let players shoot colorful paint around the arena and give out some buffs for LMGs. The hop-up is consistent with the spray paint seen on the signs and could be a part of a future teaser.

Respawn hasnt officially confirmed the next legends identity, however. Even though data miners can be extremely accurate, the information in the game files can change before being deployed to the live servers. The only way to know with full certainty is to wait until an official release, which may be drawing close.

Respawn revealed the Always Be Closing Evolved limited-time mode yesterday, which is scheduled to take place between Aug. 11 and 18. That means the next season will likely kick off in mid-to-late August.

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Apex in-game teaser sprays an R over Hammond Robotics signs in World's Edge - Dot Esports

Robotics – Wikipedia

Design, construction, operation, and application of robots

Robotics is an interdisciplinary research area at the interface of computer science and engineering.[1] Robotics involves design, construction, operation, and use of robots. The goal of robotics is to design intelligent machines that can help and assist humans in their day-to-day lives and keep everyone safe. Robotics draws on the achievement of information engineering, computer engineering, mechanical engineering, electronic engineering and others.

Robotics develops machines that can substitute for humans and replicate human actions. Robots can be used in many situations and for many purposes, but today many are used in dangerous environments (including inspection of radioactive materials, bomb detection and deactivation), manufacturing processes, or where humans cannot survive (e.g. in space, underwater, in high heat, and clean up and containment of hazardous materials and radiation). Robots can take on any form but some are made to resemble humans in appearance. This is said to help in the acceptance of a robot in certain replicative behaviors usually performed by people. Such robots attempt to replicate walking, lifting, speech, cognition, or any other human activity. Many of today's robots are inspired by nature, contributing to the field of bio-inspired robotics.

The concept of creating machines that can operate autonomously dates back to classical times, but research into the functionality and potential uses of robots did not grow substantially until the 20th century. Throughout history, it has been frequently assumed by various scholars, inventors, engineers, and technicians that robots will one day be able to mimic human behavior and manage tasks in a human-like fashion. Today, robotics is a rapidly growing field, as technological advances continue; researching, designing, and building new robots serve various practical purposes, whether domestically, commercially, or militarily. Many robots are built to do jobs that are hazardous to people, such as defusing bombs, finding survivors in unstable ruins, and exploring mines and shipwrecks. Robotics is also used in STEM (science, technology, engineering, and mathematics) as a teaching aid.[2]

Robotics is a branch of engineering that involves the conception, design, manufacture, and operation of robots. This field overlaps with computer engineering, computer science (especially artificial intelligence), electronics, mechatronics, mechanical, nanotechnology and bioengineering.[3]

The word robotics was derived from the word robot, which was introduced to the public by Czech writer Karel apek in his play R.U.R. (Rossum's Universal Robots), which was published in 1920.[4] The word robot comes from the Slavic word robota, which means slave/servant. The play begins in a factory that makes artificial people called robots, creatures who can be mistaken for humans very similar to the modern ideas of androids. Karel apek himself did not coin the word. He wrote a short letter in reference to an etymology in the Oxford English Dictionary in which he named his brother Josef apek as its actual originator.[4]

According to the Oxford English Dictionary, the word robotics was first used in print by Isaac Asimov, in his science fiction short story "Liar!", published in May 1941 in Astounding Science Fiction. Asimov was unaware that he was coining the term; since the science and technology of electrical devices is electronics, he assumed robotics already referred to the science and technology of robots. In some of Asimov's other works, he states that the first use of the word robotics was in his short story Runaround (Astounding Science Fiction, March 1942),[5][6] where he introduced his concept of The Three Laws of Robotics. However, the original publication of "Liar!" predates that of "Runaround" by ten months, so the former is generally cited as the word's origin.

In 1948, Norbert Wiener formulated the principles of cybernetics, the basis of practical robotics.

Fully autonomous robots only appeared in the second half of the 20th century. The first digitally operated and programmable robot, the Unimate, was installed in 1961 to lift hot pieces of metal from a die casting machine and stack them. Commercial and industrial robots are widespread today and used to perform jobs more cheaply, more accurately and more reliably, than humans. They are also employed in some jobs which are too dirty, dangerous, or dull to be suitable for humans. Robots are widely used in manufacturing, assembly, packing and packaging, mining, transport, earth and space exploration, surgery,[7] weaponry, laboratory research, safety, and the mass production of consumer and industrial goods.[8]

There are many types of robots; they are used in many different environments and for many different uses. Although being very diverse in application and form, they all share three basic similarities when it comes to their construction:

As more and more robots are designed for specific tasks this method of classification becomes more relevant. For example, many robots are designed for assembly work, which may not be readily adaptable for other applications. They are termed as "assembly robots". For seam welding, some suppliers provide complete welding systems with the robot i.e. the welding equipment along with other material handling facilities like turntables, etc. as an integrated unit. Such an integrated robotic system is called a "welding robot" even though its discrete manipulator unit could be adapted to a variety of tasks. Some robots are specifically designed for heavy load manipulation, and are labeled as "heavy-duty robots".[23]

Current and potential applications include:

At present, mostly (leadacid) batteries are used as a power source. Many different types of batteries can be used as a power source for robots. They range from leadacid batteries, which are safe and have relatively long shelf lives but are rather heavy compared to silvercadmium batteries that are much smaller in volume and are currently much more expensive. Designing a battery-powered robot needs to take into account factors such as safety, cycle lifetime and weight. Generators, often some type of internal combustion engine, can also be used. However, such designs are often mechanically complex and need a fuel, require heat dissipation and are relatively heavy. A tether connecting the robot to a power supply would remove the power supply from the robot entirely. This has the advantage of saving weight and space by moving all power generation and storage components elsewhere. However, this design does come with the drawback of constantly having a cable connected to the robot, which can be difficult to manage.[37] Potential power sources could be:

Actuators are the "muscles" of a robot, the parts which convert stored energy into movement.[38] By far the most popular actuators are electric motors that rotate a wheel or gear, and linear actuators that control industrial robots in factories. There are some recent advances in alternative types of actuators, powered by electricity, chemicals, or compressed air.

The vast majority of robots use electric motors, often brushed and brushless DC motors in portable robots or AC motors in industrial robots and CNC machines. These motors are often preferred in systems with lighter loads, and where the predominant form of motion is rotational.

Various types of linear actuators move in and out instead of by spinning, and often have quicker direction changes, particularly when very large forces are needed such as with industrial robotics. They are typically powered by compressed and oxidized air (pneumatic actuator) or an oil (hydraulic actuator) Linear actuators can also be powered by electricity which usually consists of a motor and a leadscrew. Another common type is a mechanical linear actuator that is turned by hand, such as a rack and pinion on a car.

A flexure is designed as part of the motor actuator, to improve safety and provide robust force control, energy efficiency, shock absorption (mechanical filtering) while reducing excessive wear on the transmission and other mechanical components. The resultant lower reflected inertia can improve safety when a robot is interacting with humans or during collisions. It has been used in various robots, particularly advanced manufacturing robots [39] and walking humanoid robots.[40][41]

Pneumatic artificial muscles, also known as air muscles, are special tubes that expand(typically up to 40%) when air is forced inside them. They are used in some robot applications.[42][43][44]

Muscle wire, also known as shape memory alloy, Nitinol or Flexinol wire, is a material which contracts (under 5%) when electricity is applied. They have been used for some small robot applications.[45][46]

EAPs or EPAMs are a plastic material that can contract substantially (up to 380% activation strain) from electricity, and have been used in facial muscles and arms of humanoid robots,[47] and to enable new robots to float,[48] fly, swim or walk.[49]

Recent alternatives to DC motors are piezo motors or ultrasonic motors. These work on a fundamentally different principle, whereby tiny piezoceramic elements, vibrating many thousands of times per second, cause linear or rotary motion. There are different mechanisms of operation; one type uses the vibration of the piezo elements to step the motor in a circle or a straight line.[50] Another type uses the piezo elements to cause a nut to vibrate or to drive a screw. The advantages of these motors are nanometer resolution, speed, and available force for their size.[51] These motors are already available commercially, and being used on some robots.[52][53]

Elastic nanotubes are a promising artificial muscle technology in early-stage experimental development. The absence of defects in carbon nanotubes enables these filaments to deform elastically by several percent, with energy storage levels of perhaps 10J/cm3 for metal nanotubes. Human biceps could be replaced with an 8mm diameter wire of this material. Such compact "muscle" might allow future robots to outrun and outjump humans.[54]

Sensors allow robots to receive information about a certain measurement of the environment, or internal components. This is essential for robots to perform their tasks, and act upon any changes in the environment to calculate the appropriate response. They are used for various forms of measurements, to give the robots warnings about safety or malfunctions, and to provide real-time information of the task it is performing.

Current robotic and prosthetic hands receive far less tactile information than the human hand. Recent research has developed a tactile sensor array that mimics the mechanical properties and touch receptors of human fingertips.[55][56] The sensor array is constructed as a rigid core surrounded by conductive fluid contained by an elastomeric skin. Electrodes are mounted on the surface of the rigid core and are connected to an impedance-measuring device within the core. When the artificial skin touches an object the fluid path around the electrodes is deformed, producing impedance changes that map the forces received from the object. The researchers expect that an important function of such artificial fingertips will be adjusting robotic grip on held objects.

Scientists from several European countries and Israel developed a prosthetic hand in 2009, called SmartHand, which functions like a real oneallowing patients to write with it, type on a keyboard, play piano and perform other fine movements. The prosthesis has sensors which enable the patient to sense real feeling in its fingertips.[57]

Computer vision is the science and technology of machines that see. As a scientific discipline, computer vision is concerned with the theory behind artificial systems that extract information from images. The image data can take many forms, such as video sequences and views from cameras.

In most practical computer vision applications, the computers are pre-programmed to solve a particular task, but methods based on learning are now becoming increasingly common.

Computer vision systems rely on image sensors which detect electromagnetic radiation which is typically in the form of either visible light or infra-red light. The sensors are designed using solid-state physics. The process by which light propagates and reflects off surfaces is explained using optics. Sophisticated image sensors even require quantum mechanics to provide a complete understanding of the image formation process. Robots can also be equipped with multiple vision sensors to be better able to compute the sense of depth in the environment. Like human eyes, robots' "eyes" must also be able to focus on a particular area of interest, and also adjust to variations in light intensities.

There is a subfield within computer vision where artificial systems are designed to mimic the processing and behavior of biological system, at different levels of complexity. Also, some of the learning-based methods developed within computer vision have their background in biology.

Other common forms of sensing in robotics use lidar, radar, and sonar.[58] Lidar measures distance to a target by illuminating the target with laser light and measuring the reflected light with a sensor. Radar uses radio waves to determine the range, angle, or velocity of objects. Sonar uses sound propagation to navigate, communicate with or detect objects on or under the surface of the water.

A definition of robotic manipulation has been provided by Matt Mason as: "manipulation refers to an agents control of its environment through selective contact.[59]

Robots need to manipulate objects; pick up, modify, destroy, or otherwise have an effect. Thus the functional end of a robot arm intended to make the effect (whether a hand, or tool) are often referred to as end effectors,[60] while the "arm" is referred to as a manipulator.[61] Most robot arms have replaceable end-effectors, each allowing them to perform some small range of tasks. Some have a fixed manipulator which cannot be replaced, while a few have one very general purpose manipulator, for example, a humanoid hand.[62]

One of the most common types of end-effectors are "grippers". In its simplest manifestation, it consists of just two fingers which can open and close to pick up and let go of a range of small objects. Fingers can for example, be made of a chain with a metal wire run through it.[63] Hands that resemble and work more like a human hand include the Shadow Hand and the Robonaut hand.[64] Hands that are of a mid-level complexity include the Delft hand.[65][66] Mechanical grippers can come in various types, including friction and encompassing jaws. Friction jaws use all the force of the gripper to hold the object in place using friction. Encompassing jaws cradle the object in place, using less friction.

Suction end-effectors, powered by vacuum generators, are very simple astrictive[67] devices that can hold very large loads provided the prehension surface is smooth enough to ensure suction.

Pick and place robots for electronic components and for large objects like car windscreens, often use very simple vacuum end-effectors.

Suction is a highly used type of end-effector in industry, in part because the natural compliance of soft suction end-effectors can enable a robot to be more robust in the presence of imperfect robotic perception. As an example: consider the case of a robot vision system estimates the position of a water bottle, but has 1 centimeter of error. While this may cause a rigid mechanical gripper to puncture the water bottle, the soft suction end-effector may just bend slightly and conform to the shape of the water bottle surface.

Some advanced robots are beginning to use fully humanoid hands, like the Shadow Hand, MANUS,[68] and the Schunk hand.[69] These are highly dexterous manipulators, with as many as 20 degrees of freedom and hundreds of tactile sensors.[70]

For simplicity, most mobile robots have four wheels or a number of continuous tracks. Some researchers have tried to create more complex wheeled robots with only one or two wheels. These can have certain advantages such as greater efficiency and reduced parts, as well as allowing a robot to navigate in confined places that a four-wheeled robot would not be able to.

Balancing robots generally use a gyroscope to detect how much a robot is falling and then drive the wheels proportionally in the same direction, to counterbalance the fall at hundreds of times per second, based on the dynamics of an inverted pendulum.[71] Many different balancing robots have been designed.[72] While the Segway is not commonly thought of as a robot, it can be thought of as a component of a robot, when used as such Segway refer to them as RMP (Robotic Mobility Platform). An example of this use has been as NASA's Robonaut that has been mounted on a Segway.[73]

A one-wheeled balancing robot is an extension of a two-wheeled balancing robot so that it can move in any 2D direction using a round ball as its only wheel. Several one-wheeled balancing robots have been designed recently, such as Carnegie Mellon University's "Ballbot" that is the approximate height and width of a person, and Tohoku Gakuin University's "BallIP".[74] Because of the long, thin shape and ability to maneuver in tight spaces, they have the potential to function better than other robots in environments with people.[75]

Several attempts have been made in robots that are completely inside a spherical ball, either by spinning a weight inside the ball,[76][77] or by rotating the outer shells of the sphere.[78][79] These have also been referred to as an orb bot[80] or a ball bot.[81][82]

Using six wheels instead of four wheels can give better traction or grip in outdoor terrain such as on rocky dirt or grass.

Tank tracks provide even more traction than a six-wheeled robot. Tracked wheels behave as if they were made of hundreds of wheels, therefore are very common for outdoor and military robots, where the robot must drive on very rough terrain. However, they are difficult to use indoors such as on carpets and smooth floors. Examples include NASA's Urban Robot "Urbie".[83]

Walking is a difficult and dynamic problem to solve. Several robots have been made which can walk reliably on two legs, however, none have yet been made which are as robust as a human. There has been much study on human inspired walking, such as AMBER lab which was established in 2008 by the Mechanical Engineering Department at Texas A&M University.[84] Many other robots have been built that walk on more than two legs, due to these robots being significantly easier to construct.[85][86] Walking robots can be used for uneven terrains, which would provide better mobility and energy efficiency than other locomotion methods. Typically, robots on two legs can walk well on flat floors and can occasionally walk up stairs. None can walk over rocky, uneven terrain. Some of the methods which have been tried are:

The zero moment point (ZMP) is the algorithm used by robots such as Honda's ASIMO. The robot's onboard computer tries to keep the total inertial forces (the combination of Earth's gravity and the acceleration and deceleration of walking), exactly opposed by the floor reaction force (the force of the floor pushing back on the robot's foot). In this way, the two forces cancel out, leaving no moment (force causing the robot to rotate and fall over).[87] However, this is not exactly how a human walks, and the difference is obvious to human observers, some of whom have pointed out that ASIMO walks as if it needs the lavatory.[88][89][90] ASIMO's walking algorithm is not static, and some dynamic balancing is used (see below). However, it still requires a smooth surface to walk on.

Several robots, built in the 1980s by Marc Raibert at the MIT Leg Laboratory, successfully demonstrated very dynamic walking. Initially, a robot with only one leg, and a very small foot could stay upright simply by hopping. The movement is the same as that of a person on a pogo stick. As the robot falls to one side, it would jump slightly in that direction, in order to catch itself.[91] Soon, the algorithm was generalised to two and four legs. A bipedal robot was demonstrated running and even performing somersaults.[92] A quadruped was also demonstrated which could trot, run, pace, and bound.[93] For a full list of these robots, see the MIT Leg Lab Robots page.[94]

A more advanced way for a robot to walk is by using a dynamic balancing algorithm, which is potentially more robust than the Zero Moment Point technique, as it constantly monitors the robot's motion, and places the feet in order to maintain stability.[95] This technique was recently demonstrated by Anybots' Dexter Robot,[96] which is so stable, it can even jump.[97] Another example is the TU Delft Flame.

Perhaps the most promising approach utilizes passive dynamics where the momentum of swinging limbs is used for greater efficiency. It has been shown that totally unpowered humanoid mechanisms can walk down a gentle slope, using only gravity to propel themselves. Using this technique, a robot need only supply a small amount of motor power to walk along a flat surface or a little more to walk up a hill. This technique promises to make walking robots at least ten times more efficient than ZMP walkers, like ASIMO.[98][99]

A modern passenger airliner is essentially a flying robot, with two humans to manage it. The autopilot can control the plane for each stage of the journey, including takeoff, normal flight, and even landing.[100] Other flying robots are uninhabited and are known as unmanned aerial vehicles (UAVs). They can be smaller and lighter without a human pilot on board, and fly into dangerous territory for military surveillance missions. Some can even fire on targets under command. UAVs are also being developed which can fire on targets automatically, without the need for a command from a human. Other flying robots include cruise missiles, the Entomopter, and the Epson micro helicopter robot. Robots such as the Air Penguin, Air Ray, and Air Jelly have lighter-than-air bodies, propelled by paddles, and guided by sonar.

Several snake robots have been successfully developed. Mimicking the way real snakes move, these robots can navigate very confined spaces, meaning they may one day be used to search for people trapped in collapsed buildings.[101] The Japanese ACM-R5 snake robot[102] can even navigate both on land and in water.[103]

A small number of skating robots have been developed, one of which is a multi-mode walking and skating device. It has four legs, with unpowered wheels, which can either step or roll.[104] Another robot, Plen, can use a miniature skateboard or roller-skates, and skate across a desktop.[105]

Several different approaches have been used to develop robots that have the ability to climb vertical surfaces. One approach mimics the movements of a human climber on a wall with protrusions; adjusting the center of mass and moving each limb in turn to gain leverage. An example of this is Capuchin,[106] built by Dr. Ruixiang Zhang at Stanford University, California. Another approach uses the specialized toe pad method of wall-climbing geckoes, which can run on smooth surfaces such as vertical glass. Examples of this approach include Wallbot[107] and Stickybot.[108]

China's Technology Daily reported on 15 November 2008, that Dr. Li Hiu Yeung and his research group of New Concept Aircraft (Zhuhai) Co., Ltd. had successfully developed a bionic gecko robot named "Speedy Freelander". According to Dr. Yeung, the gecko robot could rapidly climb up and down a variety of building walls, navigate through ground and wall fissures, and walk upside-down on the ceiling. It was also able to adapt to the surfaces of smooth glass, rough, sticky or dusty walls as well as various types of metallic materials. It could also identify and circumvent obstacles automatically. Its flexibility and speed were comparable to a natural gecko. A third approach is to mimic the motion of a snake climbing a pole.[58]

It is calculated that when swimming some fish can achieve a propulsive efficiency greater than 90%.[109] Furthermore, they can accelerate and maneuver far better than any man-made boat or submarine, and produce less noise and water disturbance. Therefore, many researchers studying underwater robots would like to copy this type of locomotion.[110] Notable examples are the Essex University Computer Science Robotic Fish G9,[111] and the Robot Tuna built by the Institute of Field Robotics, to analyze and mathematically model thunniform motion.[112] The Aqua Penguin,[113] designed and built by Festo of Germany, copies the streamlined shape and propulsion by front "flippers" of penguins. Festo have also built the Aqua Ray and Aqua Jelly, which emulate the locomotion of manta ray, and jellyfish, respectively.

In 2014 iSplash-II was developed by PhD student Richard James Clapham and Prof. Huosheng Hu at Essex University. It was the first robotic fish capable of outperforming real carangiform fish in terms of average maximum velocity (measured in body lengths/ second) and endurance, the duration that top speed is maintained.[114] This build attained swimming speeds of 11.6BL/s (i.e. 3.7m/s).[115] The first build, iSplash-I (2014) was the first robotic platform to apply a full-body length carangiform swimming motion which was found to increase swimming speed by 27% over the traditional approach of a posterior confined waveform.[116]

Sailboat robots have also been developed in order to make measurements at the surface of the ocean. A typical sailboat robot is Vaimos[117] built by IFREMER and ENSTA-Bretagne. Since the propulsion of sailboat robots uses the wind, the energy of the batteries is only used for the computer, for the communication and for the actuators (to tune the rudder and the sail). If the robot is equipped with solar panels, the robot could theoretically navigate forever. The two main competitions of sailboat robots are WRSC, which takes place every year in Europe, and Sailbot.

Though a significant percentage of robots in commission today are either human controlled or operate in a static environment, there is an increasing interest in robots that can operate autonomously in a dynamic environment. These robots require some combination of navigation hardware and software in order to traverse their environment. In particular, unforeseen events (e.g. people and other obstacles that are not stationary) can cause problems or collisions. Some highly advanced robots such as ASIMO and Mein robot have particularly good robot navigation hardware and software. Also, self-controlled cars, Ernst Dickmanns' driverless car, and the entries in the DARPA Grand Challenge, are capable of sensing the environment well and subsequently making navigational decisions based on this information, including by a swarm of autonomous robots.[36] Most of these robots employ a GPS navigation device with waypoints, along with radar, sometimes combined with other sensory data such as lidar, video cameras, and inertial guidance systems for better navigation between waypoints.

The state of the art in sensory intelligence for robots will have to progress through several orders of magnitude if we want the robots working in our homes to go beyond vacuum-cleaning the floors. If robots are to work effectively in homes and other non-industrial environments, the way they are instructed to perform their jobs, and especially how they will be told to stop will be of critical importance. The people who interact with them may have little or no training in robotics, and so any interface will need to be extremely intuitive. Science fiction authors also typically assume that robots will eventually be capable of communicating with humans through speech, gestures, and facial expressions, rather than a command-line interface. Although speech would be the most natural way for the human to communicate, it is unnatural for the robot. It will probably be a long time before robots interact as naturally as the fictional C-3PO, or Data of Star Trek, Next Generation.

Interpreting the continuous flow of sounds coming from a human, in real time, is a difficult task for a computer, mostly because of the great variability of speech.[118] The same word, spoken by the same person may sound different depending on local acoustics, volume, the previous word, whether or not the speaker has a cold, etc.. It becomes even harder when the speaker has a different accent.[119] Nevertheless, great strides have been made in the field since Davis, Biddulph, and Balashek designed the first "voice input system" which recognized "ten digits spoken by a single user with 100% accuracy" in 1952.[120] Currently, the best systems can recognize continuous, natural speech, up to 160 words per minute, with an accuracy of 95%.[121] With the help of artificial intelligence, machines nowadays can use people's voice to identify their emotions such as satisfied or angry[122]

Other hurdles exist when allowing the robot to use voice for interacting with humans. For social reasons, synthetic voice proves suboptimal as a communication medium,[123] making it necessary to develop the emotional component of robotic voice through various techniques.[124][125] An advantage of diphonic branching is the emotion that the robot is programmed to project, can be carried on the voice tape, or phoneme, already pre-programmed onto the voice media. One of the earliest examples is a teaching robot named leachim developed in 1974 by Michael J. Freeman.[126][127] Leachim was able to convert digital memory to rudimentary verbal speech on pre-recorded computer discs.[128] It was programmed to teach students in The Bronx, New York.[128]

One can imagine, in the future, explaining to a robot chef how to make a pastry, or asking directions from a robot police officer. In both of these cases, making hand gestures would aid the verbal descriptions. In the first case, the robot would be recognizing gestures made by the human, and perhaps repeating them for confirmation. In the second case, the robot police officer would gesture to indicate "down the road, then turn right". It is likely that gestures will make up a part of the interaction between humans and robots.[129] A great many systems have been developed to recognize human hand gestures.[130]

Facial expressions can provide rapid feedback on the progress of a dialog between two humans, and soon may be able to do the same for humans and robots. Robotic faces have been constructed by Hanson Robotics using their elastic polymer called Frubber, allowing a large number of facial expressions due to the elasticity of the rubber facial coating and embedded subsurface motors (servos).[131] The coating and servos are built on a metal skull. A robot should know how to approach a human, judging by their facial expression and body language. Whether the person is happy, frightened, or crazy-looking affects the type of interaction expected of the robot. Likewise, robots like Kismet and the more recent addition, Nexi[132] can produce a range of facial expressions, allowing it to have meaningful social exchanges with humans.[133]

Artificial emotions can also be generated, composed of a sequence of facial expressions and/or gestures. As can be seen from the movie Final Fantasy: The Spirits Within, the programming of these artificial emotions is complex and requires a large amount of human observation. To simplify this programming in the movie, presets were created together with a special software program. This decreased the amount of time needed to make the film. These presets could possibly be transferred for use in real-life robots.

Many of the robots of science fiction have a personality, something which may or may not be desirable in the commercial robots of the future.[134] Nevertheless, researchers are trying to create robots which appear to have a personality:[135][136] i.e. they use sounds, facial expressions, and body language to try to convey an internal state, which may be joy, sadness, or fear. One commercial example is Pleo, a toy robot dinosaur, which can exhibit several apparent emotions.[137]

The Socially Intelligent Machines Lab of the Georgia Institute of Technology researches new concepts of guided teaching interaction with robots. The aim of the projects is a social robot that learns task and goals from human demonstrations without prior knowledge of high-level concepts. These new concepts are grounded from low-level continuous sensor data through unsupervised learning, and task goals are subsequently learned using a Bayesian approach. These concepts can be used to transfer knowledge to future tasks, resulting in faster learning of those tasks. The results are demonstrated by the robot Curi who can scoop some pasta from a pot onto a plate and serve the sauce on top.[138]

The mechanical structure of a robot must be controlled to perform tasks. The control of a robot involves three distinct phases perception, processing, and action (robotic paradigms). Sensors give information about the environment or the robot itself (e.g. the position of its joints or its end effector). This information is then processed to be stored or transmitted and to calculate the appropriate signals to the actuators (motors) which move the mechanical.

The processing phase can range in complexity. At a reactive level, it may translate raw sensor information directly into actuator commands. Sensor fusion may first be used to estimate parameters of interest (e.g. the position of the robot's gripper) from noisy sensor data. An immediate task (such as moving the gripper in a certain direction) is inferred from these estimates. Techniques from control theory convert the task into commands that drive the actuators.

At longer time scales or with more sophisticated tasks, the robot may need to build and reason with a "cognitive" model. Cognitive models try to represent the robot, the world, and how they interact. Pattern recognition and computer vision can be used to track objects. Mapping techniques can be used to build maps of the world. Finally, motion planning and other artificial intelligence techniques may be used to figure out how to act. For example, a planner may figure out how to achieve a task without hitting obstacles, falling over, etc.

Control systems may also have varying levels of autonomy.

Another classification takes into account the interaction between human control and the machine motions.

Much of the research in robotics focuses not on specific industrial tasks, but on investigations into new types of robots, alternative ways to think about or design robots, and new ways to manufacture them. Other investigations, such as MIT's cyberflora project, are almost wholly academic.

A first particular new innovation in robot design is the open sourcing of robot-projects. To describe the level of advancement of a robot, the term "Generation Robots" can be used. This term is coined by Professor Hans Moravec, Principal Research Scientist at the Carnegie Mellon University Robotics Institute in describing the near future evolution of robot technology. First generation robots, Moravec predicted in 1997, should have an intellectual capacity comparable to perhaps a lizard and should become available by 2010. Because the first generation robot would be incapable of learning, however, Moravec predicts that the second generation robot would be an improvement over the first and become available by 2020, with the intelligence maybe comparable to that of a mouse. The third generation robot should have the intelligence comparable to that of a monkey. Though fourth generation robots, robots with human intelligence, professor Moravec predicts, would become possible, he does not predict this happening before around 2040 or 2050.[141]

The second is evolutionary robots. This is a methodology that uses evolutionary computation to help design robots, especially the body form, or motion and behavior controllers. In a similar way to natural evolution, a large population of robots is allowed to compete in some way, or their ability to perform a task is measured using a fitness function. Those that perform worst are removed from the population and replaced by a new set, which have new behaviors based on those of the winners. Over time the population improves, and eventually a satisfactory robot may appear. This happens without any direct programming of the robots by the researchers. Researchers use this method both to create better robots,[142] and to explore the nature of evolution.[143] Because the process often requires many generations of robots to be simulated,[144] this technique may be run entirely or mostly in simulation, using a robot simulator software package, then tested on real robots once the evolved algorithms are good enough.[145] Currently, there are about 10 million industrial robots toiling around the world, and Japan is the top country having high density of utilizing robots in its manufacturing industry.[citation needed]

The study of motion can be divided into kinematics and dynamics.[146] Direct kinematics or forward kinematics refers to the calculation of end effector position, orientation, velocity, and acceleration when the corresponding joint values are known. Inverse kinematics refers to the opposite case in which required joint values are calculated for given end effector values, as done in path planning. Some special aspects of kinematics include handling of redundancy (different possibilities of performing the same movement), collision avoidance, and singularity avoidance. Once all relevant positions, velocities, and accelerations have been calculated using kinematics, methods from the field of dynamics are used to study the effect of forces upon these movements. Direct dynamics refers to the calculation of accelerations in the robot once the applied forces are known. Direct dynamics is used in computer simulations of the robot. Inverse dynamics refers to the calculation of the actuator forces necessary to create a prescribed end-effector acceleration. This information can be used to improve the control algorithms of a robot.

In each area mentioned above, researchers strive to develop new concepts and strategies, improve existing ones, and improve the interaction between these areas. To do this, criteria for "optimal" performance and ways to optimize design, structure, and control of robots must be developed and implemented.

Bionics and biomimetics apply the physiology and methods of locomotion of animals to the design of robots. For example, the design of BionicKangaroo was based on the way kangaroos jump.

There has been some research into whether robotics algorithms can be run more quickly on quantum computers than they can be run on digital computers. This area has been referred to as quantum robotics.[147]

Robotics engineers design robots, maintain them, develop new applications for them, and conduct research to expand the potential of robotics.[148] Robots have become a popular educational tool in some middle and high schools, particularly in parts of the USA,[149] as well as in numerous youth summer camps, raising interest in programming, artificial intelligence, and robotics among students.

Universities like Worcester Polytechnic Institute (WPI) offer bachelors, masters, and doctoral degrees in the field of robotics.[150] Vocational schools offer robotics training aimed at careers in robotics.

The Robotics Certification Standards Alliance (RCSA) is an international robotics certification authority that confers various industry- and educational-related robotics certifications.

Several national summer camp programs include robotics as part of their core curriculum. In addition, youth summer robotics programs are frequently offered by celebrated museums and institutions.

There are many competitions around the globe. The SeaPerch curriculum is aimed as students of all ages. This is a short list of competition examples; for a more complete list see Robot competition.

The FIRST organization offers the FIRST Lego League Jr. competitions for younger children. This competition's goal is to offer younger children an opportunity to start learning about science and technology. Children in this competition build Lego models and have the option of using the Lego WeDo robotics kit.

One of the most important competitions is the FLL or FIRST Lego League. The idea of this specific competition is that kids start developing knowledge and getting into robotics while playing with Lego since they are nine years old. This competition is associated with National Instruments. Children use Lego Mindstorms to solve autonomous robotics challenges in this competition.

The FIRST Tech Challenge is designed for intermediate students, as a transition from the FIRST Lego League to the FIRST Robotics Competition.

The FIRST Robotics Competition focuses more on mechanical design, with a specific game being played each year. Robots are built specifically for that year's game. In match play, the robot moves autonomously during the first 15 seconds of the game (although certain years such as 2019's Deep Space change this rule), and is manually operated for the rest of the match.

The various RoboCup competitions include teams of teenagers and university students. These competitions focus on soccer competitions with different types of robots, dance competitions, and urban search and rescue competitions. All of the robots in these competitions must be autonomous. Some of these competitions focus on simulated robots.

AUVSI runs competitions for flying robots, robot boats, and underwater robots.

The Student AUV Competition Europe [151] (SAUC-E) mainly attracts undergraduate and graduate student teams. As in the AUVSI competitions, the robots must be fully autonomous while they are participating in the competition.

The Microtransat Challenge is a competition to sail a boat across the Atlantic Ocean.

RoboGames is open to anyone wishing to compete in their over 50 categories of robot competitions.

Federation of International Robot-soccer Association holds the FIRA World Cup competitions. There are flying robot competitions, robot soccer competitions, and other challenges, including weightlifting barbells made from dowels and CDs.

Many schools across the country are beginning to add robotics programs to their after school curriculum. Some major programs for afterschool robotics include FIRST Robotics Competition, Botball and B.E.S.T. Robotics.[152] Robotics competitions often include aspects of business and marketing as well as engineering and design.

The Lego company began a program for children to learn and get excited about robotics at a young age.[153]

Robotics is an essential component in many modern manufacturing environments. As factories increase their use of robots, the number of roboticsrelated jobs grow and have been observed to be steadily rising.[154] The employment of robots in industries has increased productivity and efficiency savings and is typically seen as a long term investment for benefactors. A paper by Michael Osborne andCarl Benedikt Freyfound that 47 per cent of US jobs are at risk to automation "over some unspecified number of years".[155] These claims have been criticized on the ground that social policy, not AI, causes unemployment.[156] In a 2016 article in The Guardian, Stephen Hawking stated "The automation of factories has already decimated jobs in traditional manufacturing, and the rise of artificial intelligence is likely to extend this job destruction deep into the middle classes, with only the most caring, creative or supervisory roles remaining".[157]

A discussion paper drawn up by EU-OSHA highlights how the spread of robotics presents both opportunities and challenges for occupational safety and health (OSH).[158]

The greatest OSH benefits stemming from the wider use of robotics should be substitution for people working in unhealthy or dangerous environments. In space, defence, security, or the nuclear industry, but also in logistics, maintenance, and inspection, autonomous robots are particularly useful in replacing human workers performing dirty, dull or unsafe tasks, thus avoiding workers' exposures to hazardous agents and conditions and reducing physical, ergonomic and psychosocial risks. For example, robots are already used to perform repetitive and monotonous tasks, to handle radioactive material or to work in explosive atmospheres. In the future, many other highly repetitive, risky or unpleasant tasks will be performed by robots in a variety of sectors like agriculture, construction, transport, healthcare, firefighting or cleaning services.[159]

Despite these advances, there are certain skills to which humans will be better suited than machines for some time to come and the question is how to achieve the best combination of human and robot skills. The advantages of robotics include heavy-duty jobs with precision and repeatability, whereas the advantages of humans include creativity, decision-making, flexibility, and adaptability. This need to combine optimal skills has resulted in collaborative robots and humans sharing a common workspace more closely and led to the development of new approaches and standards to guarantee the safety of the "man-robot merger". Some European countries are including robotics in their national programmes and trying to promote a safe and flexible co-operation between robots and operators to achieve better productivity. For example, the German Federal Institute for Occupational Safety and Health (BAuA) organises annual workshops on the topic "human-robot collaboration".

In the future, co-operation between robots and humans will be diversified, with robots increasing their autonomy and human-robot collaboration reaching completely new forms. Current approaches and technical standards[160][161] aiming to protect employees from the risk of working with collaborative robots will have to be revised.

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Robotics - Wikipedia

What Is Robotics? Types Of Robots | Built In

Robotics is quickly infiltrating every aspect our lives, including at home.Manufacturing

The manufacturing industry is probably the oldest and most well-known user of robots. These robots and co-bots (bots that work alongside humans) work to efficiently test and assemble products, like cars and industrial equipment. Its estimated that there are more than three million industrial robots in use right now.

Shipping, handling and quality control robots are becoming a must-have for most retailers and logistics companies. Because we now expectour packages arriving at blazing speeds, logistics companies employ robots inwarehouses, and even on the road, to help maximize time efficiency. Right now, there are robots taking your items off the shelves, transporting them across the warehouse floor and packaging them. Additionally, a rise in last-mile robots (robots that will autonomously deliver your package to your door) ensure that youll have a face-to-metal-face encounter with a logistics bot in the near future.

Its not science fiction anymore. Robots can be seen all over our homes, helping with chores, reminding us of our schedules and even entertaining our kids. The most well-known example of home robots is the autonomous vacuum cleanerRoomba. Additionally, robots have now evolved to do everything from autonomously mowing grass to cleaning pools.

Is there anything more science fiction-like than autonomous vehicles? These self-driving cars are no longer just imagination. A combination of data science and robotics, self-driving vehicles are taking the world by storm. Automakers, like Tesla, Ford, Waymo, Volkswagen and BMW are all working on the next wave of travel that will let us sit back, relax and enjoy the ride. Rideshare companies Uber and Lyft are also developing autonomous rideshare vehicles that dont require humans to operate the vehicle.

Robots have made enormous strides in the healthcare industry. These mechanical marvels have use in just about every aspect of healthcare, from robot-assisted surgeries to bots that help humans recover from injury in physical therapy. Examples of robots at work in healthcare areToyotas healthcare assistants, which help people regain the ability to walk, and TUG, a robot designed to autonomously stroll throughout a hospital and deliver everything from medicines to clean linens.

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What Is Robotics? Types Of Robots | Built In

Robotics – an overview | ScienceDirect Topics

10.3 Robotic surgery experience

Robotics overcomes many of the disadvantages of open surgery as well as those still present with laparoscopy. In a way, it embodies the natural progression in the path to MIS. The advantages include: 3D optics, wrist-like motion, tremor filtering, motion scaling, better ergonomics, and less fatigue. This translates into a lower conversion rate, decreased length of stay, easier learning curve, and the ability to operate in constricted spaces. Conversion from MIS to open has a deleterious impact on numerous patient factors, including increased transfusion rate (11.5% vs 1.9%), wound infection rate (23% vs 12%), complication rate (44% vs 21%), length of stay (+6 days vs base), and 5-year disease-free survival rate (40.2% vs 70.7%) [2426]. Recent analyses of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database comparing thousands of patients who underwent laparoscopic or robotic colorectal surgery found significantly lower conversion rates for robotics and lower length of hospital stay for both abdominal and pelvic robotic cases. There was no difference in postoperative complications when comparing the two groups and a significantly shorter length of stay for robotic procedures [27,28]. Other large database studies comparing the two groups with propensity score matching demonstrated reduced 30-day postoperative septic complications (2.3% vs 4%), hospital stay (mean: 4.8 vs 6.3 days), and discharge to another facility (3.5% vs 5.8%) in favor of robotic colectomy [29]. Analysis of the Michigan Surgical Quality Collaborative database comparing laparoscopic, hand-assisted laparoscopic, and robotic colon and rectal operations found significantly lower conversion rates for robotics in rectal resections (21.2% vs 7.8%), and approaching significance for colon resections (16.9% vs 9%) [30]. Conversion to open resulted in significantly longer length of stay for robotic (1.3 days) and laparoscopic procedures (1.7 days).

Studies have shown that the learning curve for robotic colorectal surgery ranges from 15 to 25 cases. Obtaining a learning curve which is half of that required for laparoscopy requires the surgeon to master three unique concepts of robotic surgery as outlined by Bokhari et al. [18]: (1) substituting visual cues with regard to tension and manipulation of tissues in place of tactile feedback, (2) grasping the spatial orientation of robotic instruments outside the visual field of view to maneuver safely without direct visualization, and (3) envisioning the alignment of the robotic arms and cart while operating remotely at the console, thereby minimizing external collisions [18]. A more recent study has examined whether physician factors (including time since graduation, fellowship status, and number of procedures performed) were associated with hospital stay and complications following common robotic surgery procedures in the State of New York among 1670 patients. Hospital-level factors were also analyzed, including urban versus rural setting, teaching status, hospital size, and the presence of a fellowship. After evaluating all factors in multivariable regression models and adjusting for covariates such as patients characteristics and comorbidities, neither physician- not hospital-related factors were significantly related to length of stay or complications [31]. Robotic surgery may eliminate the differences between hospitals and physicians, making outcomes independent of surgeon volume and experience.

The benefits of intracorporeal anastomosis and off-midline specimen extraction have already been demonstrated with laparoscopic colorectal surgery. This is made even easier with robotic assistance, limiting excessive handing of bowel that leads to ileus, improper orientation, and avoiding a midline extraction site. Past studies comparing laparoscopic right hemicolectomy with intracorporeal versus extracorporeal anastomosis showed decreased postoperative complications (18.7% vs 35%), infection rate (4.4% vs 14%), length of stay (mean: 5.9 vs 6.9 days), and incisional hernia rate (2.2% vs 17%) [32]. A large study examining extraction site location and incisional hernias after laparoscopic colorectal surgery has shown twice the rate of incisional hernia with midline extraction compared to off-midline (8.9% vs 2.3%4.8%) [33]. A recent multicenter retrospective study compared robotic right colectomy with intracorporeal anastomosis (RRCIA) to laparoscopic right colectomy with extracorporeal (LRCEA) and intracorporeal (LRCIA) anastomosis among 236 patients. RRCIA offers significantly better perioperative recovery outcomes compared to LRCEA, with a substantial reduction in the length of stay (4 vs 7 days). Compared with the LRCIA, the RRCIA had a shorter time to first flatus but offered no advantages in terms of the length of stay. Once again, the conversion rate was much lower for RRCIA (3.9%) versus LRCEA (8.5%) versus LRCIA (15%) [34]. This study reinforces the benefits of an intracorporeal anastomosis and the fact that it is much easier to perform robotically, leading to a decreased conversion rate.

Multiple studies have demonstrated the safety and feasibility of robotic colorectal resection with regards to short-term oncologic outcomes [35,36]. A recent retrospective study comprised of 732 patients analyzing long-term oncologic outcomes using propensity score matching showed comparable survival between robotic and laparoscopic TME. In multivariate analysis, robotic surgery was a significant prognostic factor for overall survival and cancer-specific survival [37]. The latest and largest randomized clinical trial of robotic-assisted laparoscopic surgery for patients with rectal adenocarcinoma (ROLARR) demonstrated comparable oncologic outcomes to previously published large randomized trials. The positive circumferential resection margin rate (5.7%) was lower than previous trials studying conventional laparoscopy (ACOSOG Z6051, 12.1%; ALaCaRT, 7%). Pathological grading of intact mesorectum (75.3%) was comparable to ACOSOG Z6051 (72.9%). Surprisingly, there was no statistically significant difference in the rate of conversion to open laparotomy for robotic compared with laparoscopic surgery (8.1% vs 12.2%) [38]. The authors attributed this to surgeons having varying robotic experience as compared to the expert laparoscopic group. The fact that less experienced robotic surgeons had the same conversion rate as expert laparoscopists supports the previously mentioned study by Altieri et al. which did not find surgeon robotic experience tied to outcomes or length of stay, in contrast to laparoscopy [31].

Disadvantages of robotic surgery include: increased operative time, lack of haptic feedback, surgeons remote location away from the operating room table, inability to perform multiquadrant abdominal surgery, and the cost of technology [3841]. Several metaanalyses and a most recent ACS NSQIP database analysis have compared operative times for robotic versus laparoscopic colorectal resections with a mean operative time of approximately 40minutes longer for robotic colorectal resection when compared to laparoscopic [28,42,43]. Longer operative times have been shown to improve with surgeon experience, some single-surgeon studies demonstrating a statistically significant decrease in mean operative time from 267 to 224minutes [44]. However, larger randomized studies analyzing surgeons with varying robotic experience still showed prolonged operating time when compared to laparoscopy [38]. With experience, visual cues substitute for haptic feedback, thus avoiding excessive tissue manipulation and injury. Numerous studies, previously discussed, have shown the safety and feasibility of robotic surgery with equivalent or decreased complications compared to laparoscopic surgery, thus making the lack haptic feedback a nonsafety issue. One can postulate that with haptic feedback operative time may be reduced but this will require implementation and further study of such technology. Seasoned first assists and a well-trained robotics team can provide confidence and feedback at the bedside for the surgeon while he or she is at the console, minimizing the issue of not being at the patient bedside. It behooves the surgeon to train his or her team and have an action plan in case of emergency bleeding or need to convert to open laparotomy.

Finally, the cost of new technology is offset with increased case volume, instrument use optimization, and previously touted clinical benefits. However, this remains a controversial issue since acquiring the latest robotic system costs $1.85$2.3 million and does not include ongoing instrument and maintenance costs, which can range from $0.08 to $0.17 million/year. The ROLARR randomized clinical trial comparing robotic to laparoscopic rectal surgery suggested that robotic surgery for rectal cancer is unlikely to be cost-saving. The mean difference per operation, excluding the acquisition and maintenance costs, was $1132 driven by longer operating room time and increased cost for robotic instruments [38,45]. In contrast, a recent study examining surgeons with higher experience in robotic and laparoscopic colorectal procedures (30 or more robotic procedures per year) showed no statistically significant difference in total direct cost. When comparing supply costs, robotic surgery was more expensive than laparoscopic surgery (mean: $764) due to increased costs associated with robotic reusable instruments. The total direct costs were comprised of supplies, hospital stay, and operating room costs and showed no difference ($24,473 vs $24,343) likely due to reduced length of stay and lower conversion rate [46]. Cheaper cost can be attained by decreasing operative time, limiting superfluous robotic instrument use, and improving utilization of the robotic system.

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NMSU’s Arrowhead Center signs agreement with Minerva Robotics to bring gourmet tortillas to masses – El Paso Herald-Post

When new technology meets ancient and revered culinary traditions, even classic handmade foods can be improved upon and made more efficiently.

Minerva Robotics, with the help of New Mexico State Universitys Arrowhead Center, aims to use computer learning and fresh ingredients to bring gourmet tortillas to homes and businesses in the United States and Mexico.

Minerva has shown an impressive skill set to launch a startup, developing a prototype, connect with local resources, and fundraising, said Carlos Murguia, director of Arrowhead Centers Foster Innovation Exchange (FIX) program. In July, Arrowhead Centers FIX signed an agreement with Minerva Robotics to continue their journey.

Minerva will be creating the first-of-its-kind tortilla subscription service. Customers will be able to subscribe and receive freshly made tortillas delivered to their homes or businesses.

With robotics, Minerva wants to tailor the use of raw materials, like New Mexico heirloom corn, to each customers specifications instead of the typically used, highly processed flours commonly used.

Minervas smart tortilla machine, the NixMix, will take high-quality corn in order to replicate the handmade process of tortilla production. It gets its name from nixtamalization, the process by which corn kernels are cooked in an alkaline solution, changing the corns chemical structure. It is a critical step that gives tortillas its flavor and texture.

Unfortunately, its a labor- and time-intensive method taking up to nine hours from milling the corn to the hot tortilla on the table.

While there are machines pumping out regular store-bought tortillas, the heavily processed ingredients are not like what is made at a home a flavor and consistency that the NixMix tortilla matches.

Whats in use now are outdated machines, unchanged technology from 50 years ago with a lot of inefficiency, said J.R. Rosillo, CEO of Minerva Robotics, who has been launching startups for the past 3 years. We want to cater to a growing Hispanic market in the U.S. Its the largest minority, approximately 18 percent of the U.S. population. We have an initial target of 50,000 Mexican restaurants in the U.S. and over 80,000 tortilla shops in Mexico with our product.

Rosillo, along with Chief Marketing Officer Renata Salcedo, Chief Technology Officer Marco Moreno and Country Director Fernando Nuez, will merge their resources with those of Arrowhead Center to make the move into the Mexican and United States markets.

Arrowhead is able to offer a soft landing for Minerva to launch the startup in New Mexico and take full advantage of our network of advisors who can guide the way, said Kathryn Hansen, director of Arrowhead Center. Minerva already has had the support of NMSU faculty to discuss different types of New Mexico-grown corn that would be a selling point for not only the product, but also valuable for our states economic development abroad.

Minerva Robotics looks to hire students and recent graduates of NMSU and become advisers for those interested in engaging the Mexican market with the benefits of the home base in New Mexico.

New Mexico is a fertile territory where community, agricultural diversity, and collaboration will create a scenario of innovation and progress, said Rosillo. Salcedo added, For us, we want to share, through technology, our traditional tortilla-making methods with the world.

For more information about Minerva Robotics, click here. To learn more about Arrowhead Centers FIX program, the programs website

Author:Cassie McClure NMSU

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NMSU's Arrowhead Center signs agreement with Minerva Robotics to bring gourmet tortillas to masses - El Paso Herald-Post

Food Robotics Market Size 2020 Explosive Factors of Revenue by Major Manufacturers listed in Industry are- Mitsubishi Electric, ABB, Kawasaki Heavy,…

Food Robotics Market 2020-2027

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Thestudy considers the Food RoboticsMarketvalue and volume generated from the sales of the following segments:Major Marketmanufacturerscovered in the Food RoboticsMarketare:Mitsubishi Electric Corporation, ABB, Kawasaki Heavy Industries, Fanuc Corporation, Rockwell Automation, Inc, KUKA AG, Seiko Espon Corporation, YASKAWA ELECTRIC CORPORATION, Stubli International AG., Mycom and Universal Robotic and Bastian Solutions among others.

Based on regions, the Food RoboticsMarketis classified into North America, Europe, Asia- Pacific, Middle East & Africa, and Latin AmericaMiddle East and Africa (GCC Countries and Egypt)North America (United States, Mexico, and Canada)South America(Brazil, Argentina etc.)Europe(Turkey, Germany, Russia UK, Italy, France, etc.)Asia-Pacific(Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)

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Food robotics market is expected to grow at USD 1.4 billion at a growth rate of 12.90% in the forecast period of 2020 to 2027. The growing attention on increasing practical efficiency in production and raising the demand of packed foods are foreseen to drive the growth of the market.

However, the sudden change in the robotics technology and the addition of innovative and advanced automation technology is compelling the demand for robotics systems in the food industry. These technologies help users in the automation to drive or to enhance the industrial application such as palletizing, packaging and processing. Rise in production of low-cost robots and increasing the functionality of robots will enhance the growth of food robotics market, where as the scarcity of skilled workforce in emerging economies act as a restrain to the market.

Highlights of TOC:

Overview:In addition to an overview of the Food RoboticsMarket, this section provides an overview of the report to give an idea of the type and content of the study.

Market dynamics:Here the authors of the report discussed in detail the main drivers, restrictions, challenges, trends and opportunities in the market.

Product Segments:This part of the report shows the growth of the market for various types of products sold by the largest companies.

Application segments: The analysts who have authored the report have thoroughly evaluated the market potential of the key applications and identified the future opportunities they should create in the Food Robotics Market.

Geographic Segments:Each regional market is carefully examined to understand its current and future growth scenarios.

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Food Robotics Market Size 2020 Explosive Factors of Revenue by Major Manufacturers listed in Industry are- Mitsubishi Electric, ABB, Kawasaki Heavy,...

Indoor Robots Market Analysis By Distribution Channel, Region And Forecast From 2020 To 2025|iRobot Corporation, Aethon, Ecovacs, Cobalt Robotics,…

Note: Due to the pandemic, we have included a special section on the Impact of COVID 19 on the Indoor RobotsMarket which would mention How the Covid-19 is Affecting the Industry, Market Trends and Potential Opportunities in the COVID-19 Landscape, Key Regions and Proposal for Indoor Robots Market Players to battle Covid-19 Impact.

The Indoor RobotsMarket report is compilation of intelligent, broad research studies that will help players and stakeholders to make informed business decisions in future. It offers detailed research and analysis of key aspects of the Indoor Robots market. Readers will be able to gain deeper understanding of the competitive landscape and its future scenarios, crucial dynamics, and leading segments of the global Indoor Robots market. Buyers of the report will have access to accurate PESTLE, SWOT and other types of analysis on the global Indoor Robots market. Moreover, it offers highly accurate estimations on the CAGR, market share, and market size of key regions and countries. Players can use this study to explore untapped Indoor Robots markets to extend their reach and create sales opportunities.

The study encompasses profiles of major Companies/Manufacturers operating in the global Indoor Robots Market.Key players profiled in the report include:iRobot Corporation, Aethon, Ecovacs, Cobalt Robotics, SoftBank Robotics Group, GeckoSystems International Corporation, InTouch Technologies, Simbe Robotics, Inc., NXT Robotics Corporation, Omron Adept Technologies, Savioke, Inc. and More

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Segmental Analysis:The report has classified the global Indoor Robots market into segments including product type and application. Every segment is evaluated based on share and growth rate. Besides, the analysts have studied the potential regions that may prove rewarding for the Indoor Robots manufcaturers in the coming years. The regional analysis includes reliable predictions on value and volume, there by helping market players to gain deep insights into the overall Indoor Robots industry.

Market Segment By Type:Medical RobotCleaning RobotEntertainment RobotSecurity & Surveillance RobotEducation and Research RobotPersonal Assistant RobotPublic Relation Robot

Market Segment By Application:CommercialResidential

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The authors of the report have analyzed both developing and developed regions considered for the research and analysis of the global Indoor Robots market. The regional analysis section of the report provides an extensive research study on different regional and country-wise Indoor Robots industry to help players plan effective expansion strategies.

Regions Covered in the Global Indoor Robots Market: The Middle East and Africa (GCC Countries and Egypt) North America (the United States, Mexico, and Canada) South America (Brazil etc.) Europe (Turkey, Germany, Russia UK, Italy, France, etc.) Asia-Pacific (Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)

Years Considered to Estimate the Market Size:History Year: 2015-2019Base Year: 2019Estimated Year: 2020Forecast Year: 2020-2025

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Indoor Robots Market Analysis By Distribution Channel, Region And Forecast From 2020 To 2025|iRobot Corporation, Aethon, Ecovacs, Cobalt Robotics,...

Robots And The Future of Work: Timeline – Verdict

From the introduction of the assembly line in the automobile industry in 1913 to Amazon reaching 200,000 robots working in its warehouses in 2020, the past century has seen an unprecedented level of technological progress in the workplace. Since the Industrial Revolution, the role of machines has been controversial, raising hope for progress as well as fear of change. However, despite its rapid pace, automation has not made human labour obsolete. An MIT study revealed that the employment-to-population ratio rose during the 20th century.

1913 Henry Ford installed the first moving assembly line, revolutionising the manufacturing process.

1920 Czech author Karel Capek used the term robot in his play R.U.R.

1926 A general strike in the UK, protesting wage reductions and poor working conditions, lasted for nine days.

1927 Fritz Langs film Metropolis included the character of Maria, one of the first robots depicted in cinema.

1930 The phrase technological unemployment appeared in a book by economist J.M Keynes.

1946 ENIAC, the first electronic general purpose computer, was switched on to calculate artillery firing tables.

1948 William Grey Walter built the first autonomous robots, pioneering the field of cybernetics.

1950 Alan Turing devised a way to measure the intelligence of a machine.

1959 John McCarthy and Marvin Minsky founded the MIT AI Lab.

1961 Unimate, the first industrial robot, began work on the General Motors assembly line.

1961 IBM introduced the electric typewriter, improving typists speed and productivity.

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1964 IBM launched the System/360 family of mainframe computer systems.

1967 Military strategist Herman Kahn warned of technologys potential to enable authoritarian surveillance.

1968 The film 2001: A Space Odyssey imagined a sentiment machine with intelligence that matched that of humans.

1970 SRI Internationals Shakey became the first mobile robot controlled by AI (connected to it using a radio link).

1972 Tokyos Waesda University developed Wabot-1, the first full-scale humanoid robot.

1981 The Japanese government set aside $850m for a project to develop a fifth-generation computer.

1989 UK computer scientist Tim Berners-Lee invented the World Wide Web.

1996 Honda launched the P2 humanoid robot.

1997 IBMs Deep Blue defeated world chess champion, Garry Kasparov.

2003 Skype was founded by Niklas Zennstrm and Janus Friis and developed in Estonia.

2005 A Stanford robot drove autonomously for 131 miles along an unrehearsed desert trial.

2007 Apple launched the first iPhone, creating the mobile internet as we know it today.

2009 Google started testing robot cars on roads.

2010 Facebook began using facial recognition to help tag photos.

2011 IBMs Watson defeated TV game show Jeopardy!s two greatest champions.

2011 Apples virtual assistant, Siri, appears in the iphone 4S.

2012 Rethink Robotics unveiled Baxter, its collaborative robot designed to work alongside humans.

2013 The Slack collaboration tool was launched.

2016 Google DeepMinds AlphaGo algorithm beats world Go champion Lee Sedol.

2018 Thousands of Google staff across the world staged walkouts targeting workplace culture.

2020 Amazon reportedly had 200,000 robots in operation in its US warehouses.

2020 The Covid-19 pandemic forced millions of people to start working remotely.

2022 The shared workplace model will run out of steam due to the pandemic.

2025 Remote work will become commonplace, one of the lasting legacies of Covid-19.

2030 Despite widespread anxiety, the Future of Work (FoW) will not lead to mass unemployment.

This is an edited extract from the The Future of Work Thematic Research report produced by GlobalData Thematic Research.

GlobalData is this websites parent business intelligence company.

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Robots And The Future of Work: Timeline - Verdict

High Demand for Robotics Skills in Post-Corona Recovery – Reports IFR – Business Wire

FRANKFURT, Germany--(BUSINESS WIRE)--By 2022, an operational stock of almost 4 million industrial robots are expected to work in factories worldwide. These robots will play a vital role in automating production to speed up the post-Corona economy. At the same time, robots are driving demand for skilled workers. Educational systems must effectively adjust to this demand, says the International Federation of Robotics.

Governments and companies around the globe now need to focus on providing the right skills necessary to work with robots and intelligent automation systems, says Milton Guerry, President of the International Federation of Robotics. This is important to take maximum advantage of the opportunities that these technologies offer. The post-Corona recovery will further accelerate the deployment of robotics. Policies and strategies are important to help workforces make the transition to a more automated economy.

EIU index

According to the automation readiness index published by The Economist Intelligence Unit (EIU), only four countries have already established mature education policies to deal with the challenges of an automated economy. South Korea is the category leader, followed by Estonia, Singapore and Germany. Countries like Japan, the US and France are developed and China was ranked as emerging. The EIU summed up the order of the day for governments: more study, multi-stakeholder dialogue and international knowledge sharing.

Education

Robot suppliers support the education of the workforce with practice-oriented training. Re-training the existing workforce is only a short-term measure. We must already start way earlier curricula for schools and undergraduate education need to match the demand of the industry for the workforce of the future. Demand for technical and digital skills is increasing, but equally important are cognitive skills like problem-solving and critical thinking, says Dr. Susanne Bieller, IFRs General Secretary. Economies must embrace automation and build the skills required to profit - otherwise they will be at a competitive disadvantage.

IFR Executive Round Table automatica Munich, December 2020

The topic Next Generation Workforce - Upskilling for Robotics" will be discussed by the IFR Executive Round Table on December 9 at the worlds leading trade fair for smart automation and robotics automatica in Munich.

Please find the full text version here: https://ifr.org/ifr-press-releases/

About IFR

The International Federation of Robotics: http://www.ifr.org

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High Demand for Robotics Skills in Post-Corona Recovery - Reports IFR - Business Wire

WiBotic Receives Industry-First FCC Approval for High Power Wireless Charging of Robots – Unite.AI

Matt Carlson is the Vice President of Business Development at WiBotic Inc, a company that provides reliable wireless power solutions to charge aerial, mobile and aquatic robot systems.

Why are wireless charging solutions so important to the future of robotics?

Robots need the ability to autonomously charge for most applications. It simply isnt cost effective to hire a staff of workers to manage battery charging or battery swapping. However, most autonomous charging today is done using docking stations that require physical mating of electrical contacts.

This requires very precise navigation into the charging dock which is difficult to program and is not always reliable. Failing to properly align the contacts can mean a missed charging cycle and robot downtime. Contact based stations will also wear out over time, or the contacts may become dirty or corroded again resulting in inconsistent charging. Finally, robot OEMs use a wide range of electrical contact types, making it nearly impossible to have a single charging station that can charge any robot.

Wireless systems have none of these issues.WiBoticsystems offer several centimeters of alignment tolerance, so its not necessary to have an extremely precise navigation stack. Because the antennas can be fully sealed to the elements and dont make physical contact with one another, wireless systems are also highly reliable and can handle an unlimited number of charge cycles. Finally, as robot use grows, most companies will employ more than one type of robot. Rather than having a wall or room dedicated to many different charging docks, a single wireless charging station can recharge any robot that is retrofitted with a simple receiver antenna, saving money and space.

Wibotics initial focus was on powering medical devices, what was the reason to pivot towards robots, drones, and Autonomous Underwater Vehicles (AUVs)?

WiBotics two founders, Ben Waters and Josh Smith, did indeed focus on wireless power for medical devices during much of their research at the University of Washington. Their technology increased the range and reliability of wireless power, which were both critical for the medical market. However, when Ben received his PhD and foundedWiBotic, the company immediately focused on robotics as its primary market. This was based on demand from the robotics industry.

Robot and drone OEMs and end-users recognized the benefits ofWiBotictechnology in terms of power level and range when compared with other wireless systems. They were also beginning to struggle with the deployment of contact-based chargers for large fleets of robots and were looking for more reliable solutions.

For the drone market, contact based charging is a non-starter in most cases since drones operate outdoors (mostly) where water becomes an issue with any physical electrical contacts. And, of course, underwater applications also benefit from the fully sealed nature of wireless power.

What are the power transfer technologies being used?

WiBoticuses elements of both electrical induction and magnetic resonance for power transfer. These two methods are relatively well proven at a wide range of power levels. What setsWiBoticapart is our ability to manage the connection (technically the impedance) between antennas in real time. We call this Adaptive Impedance Matching.

One of the biggest challenges with wireless power, especially for robotics, is that the electrical environment is constantly changing. If the robot docks in a slightly different position, if its internal electronics turn on and off during charging, and as the battery itself charges up, the impedance between the transmit and receive sides of the system changes. This can dramatically affect efficiency and range. Our AIM technology constantly monitors changes in impedance so we can maintain efficiency and power levels, even as all of those other elements in the system are changing.

Could you discuss the efficiency of the units, such as how much power is lost during power transmission?

ForWiBotics 250-300 Watt systems we have an end-to-end efficiency level of between 70% and 80%. This represents the full system efficiency from the input to our transmitter all the way to the output to the battery. The actual antenna-to-antenna portion of that equation is about 95% efficient, but there are losses in the transmitter circuitry and also in the battery charging circuitry. That last part is important to note since even a very well designed plug in battery charger is typically only around 90-95% efficient.

Using a wireless system like ours therefore results in about 10% less efficiency than the status quo of contact based charging.

What are the distance constraints with how close the robotic unit needs to be near the power source?

This depends on the size of the antennas used. Our standard transmitter antenna is 20cm in diameter and the receiver antenna is 10cm in diameter. With those antenna sizes, we allow for 5cm of face-to-face air gap between antennas and up to 5cm of side-to-side offset from a concentric position (so 10 total cm of side to side range).

Unlike other wireless power systems, and due to our AIM technology, we deliver full power to the battery at any point within that range. Ranges can be increased by increasing the diameter of the antennas. Because our antennas are relatively simple PCBAs (which are also very thin and lightweight) were able to modify and produce custom versions of them relatively inexpensively for customers who prefer a different size.

Are multiple robots able to use the same charging station?

Absolutely! Only one robot can charge at a wireless charging station at a time, but entire fleets of diverse robots can all share the same charging station (or set of charging stations). This is possible because, unlike most contact based chargers, the transmitter station is not sending out a specific voltage and current level. Instead it is sending wireless power at a designated frequency. Our Onboard Charger, installed on the robot, then converts that wireless energy into the specific voltage and current needed by that vehicle.

We support batteries from 0-60V and current levels from 0-30A with our current product line.

Could you discuss some of the power optimization software that is currently offered?

Our wireless power hardware ships with a web-based GUI that allows customers to configure the system for a wide range of parameters. For instance, users can choose to charge to the typical 100% charge level for a particular battery. But if they do this every time, they may not get as many charge cycles out of the battery. So if 100% charge isnt needed, the maximum voltage level can be adjusted downward to extend battery lifespan.

Similarly, if the battery is always charged with the maximum current (amps) its lifespan will be reduced. Using our GUI and APIs, users can actually proactively schedule charging so they charge as fast as possible when the robot needs to get back into service, or more slowly when they know they have more time (overnight for example). These configurability and battery optimization features are available with our standard GUI and by using our APIs.

We also offer a new software product that allows users to map and then aggregate charging information from across and entire fleet ofWiBotictransmitters and receivers. This allows robots to know when and where charging stations are available to help them maximize uptime. It also allows detailed reporting on the charging performance of batteries over time, helping identify battery issues and optimizing power delivery across the entire fleet. These features become particularly useful if the end-user is able to implement opportunity charging schemes, where robots are charging many times per day for shorter periods of time, rather than leaving service for several hours at a time for charging.

Offering wireless power to Autonomous Underwater Vehicles (AUVs) seems like it would be extremely challenging, could you discuss this?

Yes, there are definitely many challenges with underwater applications. From a power transfer perspective a couple centimeters of saltwater will attenuate power transfer by about 50%, so it will take longer to charge the same sized batteries underwater than it would in air.

The antenna range is also more restricted for that same reason, which means the UAV must have very good navigation to successfully find and dock at the charging station. This is usually aided by some sort of physical alignment device that directs the UAV into the charging station and helps to align the antennas.

The benefit of wireless power underwater however, is that the antennas can be fully potted or sealed.WiBoticsystems are currently operating at the MBARI MARS research station off the coast of Monterey, CA at a depth of nearly 3000ft. In that case, the transmitter and receiver electronics are housed in 1atm pressure bottles, but electronics can also be designed for oil filled enclosures to withstand even greater depth.

WiBoticcontinues to work with the DoD, various universities, non-profits and commercial partners to expand the use of our systems underwater, but it is definitely a challenging environment!

WiBotic has recently announced equipment authorization from the Federal Communications Commission (FCC) for its high power transmitters and receivers. These products are the first systems operating at up to 300 Watts to receive FCC approval for use in mobile robots, drones, and other industrial devices. Why is this important and what does this mean for the future of robotics and drones?

As the robotics industry continues to grow, OEMs and robot end-users are facing an increasing level of regulation and stricter safety requirements. Its important for our customers to know that WiBotic products, as a component within their larger robotic solutions, will meet those regulatory requirements. In short, it allows robot and drone manufacturers to focus on additional features and functionality for end-users rather that dealing with certification questions. This will let them deploy larger fleets faster than would otherwise be possible.

Is there anything else that you would like to share aboutWibotic?

Because most people think of the physical antennas and circuit boards when they think of wireless power, the immense amount of work we have put into our software and firmware is often overlooked. In many ways, it is the advanced firmware weve developed that allows our hardware to perform at such useful ranges and power levels.

Were also continuing to add to our fleet power optimization software capabilities to allow for even greater analysis and benchmarking of the use of power and durability of batteries across a wide range of robotic applications.

Thank you for the great interview, readers who wish to learn more should visit at WiBotic Inc, or read about how WiBotic Received an Industry-First FCC Approval for High Power Wireless Charging of Robots & drones.

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WiBotic Receives Industry-First FCC Approval for High Power Wireless Charging of Robots - Unite.AI

What Robots Need to Succeed: Machine-Learning to Teach Effectively – Robotics Business Review

With machine learning, algorithms are automatically generated from large datasets, speeding the development and reducing the difficulty of creating complex systems, including robotics systems. While data at scale is what makes accurate machine learning go, the data used to train ML models must also be very accurate and of high quality.

By Hyun Kim | July 31, 2020

The Mid-twentieth century sociologist David Reisman was perhaps the first to wonder with unease what people would do with all of their free time once the encroaching machine automation of the 1960s liberated humans from their menial chores and decision-making. His prosperous, if anxious, vision of the future only half came to pass however, as the complexities of life expanded to continually fill the days of both man and machine. Work alleviated by industrious machines, such as robotics systems, in the ensuing decades only freed humans to create increasingly elaborate new tasks to be labored over. Rather than give us more free time, the machines gave us more time to work.

Machine LearningToday, the primary man-made assistants helping humans with their work are decreasingly likely to take the form of an assembly line of robot limbs or the robotic butlers first dreamed up during the era of the Space Race. Three quarters of a century later, it is robotic minds, and not necessarily bodies, that are in demand within nearly every sector of business. But humans can only teach artificial intelligence so much or at least at so great a scale. Enter Machine Learning, the field of study in which algorithms and physical machines are taught using enormous caches of data. Machine learning has many different disciplines, with Deep Learning being a major subset of that.

Today Deep Learning is finally experiencing its star turn, driven by the explosive potential of Deep Neural Network algorithms and hardware advancements.

Deep Learning ArrivesDeep Learning utilizes neural network layers to learn patterns from datasets. The field was first conceived 20-30 years ago, but did not achieve popularity due to the limitations of computational power at the time. Today Deep Learning is finally experiencing its star turn, driven by the explosive potential of Deep Neural Network algorithms and hardware advancements. Deep Learning require enormous amounts of computational power, but can ultimately be very powerful if one has enough computational capacity and the required datasets.

So who teaches the machines? Who decides what AI needs to know? First, engineers and scientists decide how AI learns. Domain experts then advise on how robots need to function and operate within the scope of the task that is being addressed, be that assisting warehouse logistics experts, security consultants, etc.

Planning and LearningWhen it comes to AI receiving these inputs, it is important to make the distinction between Planning and Learning. Planning involves scenarios in which all the variables are already known, and the robot just has to work out at what pace it has to move each joint to complete a task such as grabbing an object. Learning on the other hand, involves a more unstructured dynamic environment in which the robot has to anticipate countless different inputs and react accordingly.

Learning can take place via Demonstrations (Physically training their movements through guided practice), Simulations (3D artificial environments), or even by being fed videos or data of a person or another robot performing the task it is hoping to master for itself. The latter of these is a form of Training Data, a set of labeled or annotated datasets that an AI algorithm can use to recognize and learn from. Training Data is increasingly necessary for todays complex Machine Learning behaviors. For ML algorithms to pick up patterns in data, ML teams need to feed it with a large amount of data.

Accuracy and AbundanceAccuracy and abundance of data are critical. A diet of inaccurate or corrupted data will result in the algorithm not being able to learn correctly, or drawing the wrong conclusions. If your dataset is focused on Chihuahuas, and you input a picture of a blueberry muffin, then you would still get a Chihuahua. This is known as lack of proper data distribution.

Insufficient training data will result in a stilted learning curve that might not ever reach the full potential of how it was designed to perform. Enough data to encompass the majority of imagined scenarios and edge cases alike is critical for true learning to take place.

Hard at WorkMachine Learning is currently being deployed across a wide array of industries and types of applications, including those involving robotics systems. For example, unmanned vehicles are currently assisting the construction industry, deployed across live worksites. Construction companies use data training platforms such as Superb AI to create and manage datasets that can teach ML models to avoid humans and animals, and to engage in assembling and building.

In the medical sector, research labs at renowned international universities deploy training data to help computer vision models to recognize tumors within MRIs and CT Scans. These can eventually be used to not only accurately diagnose and prevent diseases, but also train medical robots for surgery and other life-saving procedures. Even the best doctor in the world has a bad nights sleep sometimes, which can dull focus the next day. But a properly trained robotic tumor-hunting assistant can at perform peak efficiency every day.

Living Up to the PotentialSo whats at stake here? Theres a tremendous opportunity for training data, Machine Learning, and Artificial Intelligence to help robots to live up to the potential that Reisman imagined all those decades ago. Technology companies employing complex Machine Learning initiatives have a responsibility to educate and create trust within the general public, so that these advancements can be permitted to truly help humanity level up. If the world can deploy well-trained, built and purposed AI, coupled with advanced robotics, then we may very well live to see some of that leisure time that Reisman was so nervous about. I think most people today would agree that we certainly could use it.

Hyun Kim, Co-founder and CEO, Superb AI

Hyunsoo (Hyun) Kim is the co-founder and CEO of Superb AI, and is on a mission to democratize data and artificial intelligence. With a background in Deep Learning and Robotics during his PhD studies at Duke University and career as a Machine Learning Engineer, Kim saw the need for a more efficient way for companies to handle machine learning training data. Superb AI enables companies to create and manage the enormous amounts of data they need to train machine learning algorithms, and lower the hurdle for industries to adopt the technology. Kim has also been selected as the featured honoree for the Enterprise Technology category of Forbes 30 Under 30 Asia 2020, and Superb AI managed last year to join Y Combinator, a prominent Silicon Valley startup accelerator.

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What Robots Need to Succeed: Machine-Learning to Teach Effectively - Robotics Business Review

Microbot Medical Appoints the Co-Founder of Corindus Vascular Robotics to its Board of DirectorsVascular Interventions Executive Will Contribute…

HINGHAM, Mass., Aug. 03, 2020 (GLOBE NEWSWIRE) -- Microbot Medical Inc. (Nasdaq: MBOT) has further strengthened the Companys capabilities and expertise as Mr. Tal Wenderow, an experienced medical device and robotics executive with a proven track record in small and mid-size companies, has been appointed to the Company's Board of Directors. Mr. Wenderow co-founded Corindus Vascular Robotics, a robotic-assisted vascular interventions company, and contributed to the companys success, leading to its $1.1 billion acquisition by Siemens Healthineers AG in October 2019.

Consistent and aligned with our strategic objectives, one of which is enhancing our core leadership capabilities, Tals leadership and proven track record will contribute greatly to the future success of Microbot, commented Harel Gadot, CEO, President and Chairman. His contributions to Corindus growth, from inception through the recently completed acquisition by Siemens Healthineers AG, are well chronicled. I welcome him to the Board and look forward to his many contributions as we progress our multi-generation product portfolio, and especially the LIBERTY Robotic system given his extensive knowledge in the vascular interventional market.

With over 19 years of industry experience, Mr. Wenderow holds multiple patents and is a recognized thought leader in the vascular interventions market. He is currently the President and CEO of Vocalis Health, a global technology leader in vocal biomarkers developing voice-enabled AI solutions to create proprietary vocal biomarkers for personalized healthcare screening and continuous remote monitoring of health by using a simple voice sample. At Corindus, Mr. Wenderow served several executive leadership roles, including Chief Executive Officer and Executive Vice President of International & Business Development, and demonstrated strong business execution to achieve the companys strategic objectives. Mr. Wenderow holds a B.Sc. summa cum laude in Mechanical Engineering from Technion in Israel and has completed the Executive Program for Life Sciences at the Merage Foundation, Merage Business School, University of California, Irvine, CA.

I am extremely excited to join the Microbot Board of Directors and support the next revolution of the healthcare robotic space, commented Mr. Wenderow. Microbot is developing a portfolio of innovative medical robotic devices that have the potential to address sizeable market opportunities. The depth of the entire team is very impressive including Professor Moshe Shoham, who is a known leader and innovator in the robotic market. I look forward to collaborating and working with each of them to achieve Microbots objectives.

About Microbot Medical

Microbot Medical Inc. (NASDAQ: MBOT) is a pre-clinical medical device company that specializes in transformational micro-robotic technologies, focused primarily on both natural and artificial lumens within the human body. Microbots current proprietary technological platforms provide the foundation for the development of a Multi Generation Pipeline Portfolio (MGPP).

Microbot Medical was founded in 2010 by Harel Gadot, Prof. Moshe Shoham, and Yossi Bornstein with the goals of improving clinical outcomes for patients and increasing accessibility through the use of micro-robotic technologies. Further information about Microbot Medical is available at http://www.microbotmedical.com.

Safe Harbor

Statements pertaining to the registered direct offering, timing, the amount and anticipated use of proceeds and statements pertaining to future financial and/or operating results, future growth in research, technology, clinical development, and potential opportunities for Microbot Medical Inc. and its subsidiaries, along with other statements about the future expectations, beliefs, goals, plans, or prospects expressed by management, constitute forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995 and the Federal securities laws. Any statements that are not historical fact (including, but not limited to statements that contain words such as will, believes, plans, anticipates, expects and estimates) should also be considered to be forward-looking statements. Forward-looking statements involve risks and uncertainties, including, without limitation, market conditions and the satisfaction of customary closing conditions, risks inherent in the development and/or commercialization of potential products, including LIBERTY, the outcome of its studies to evaluate the SCS and other existing and future technologies, uncertainty in the results of pre-clinical and clinical trials or regulatory pathways and regulatory approvals, uncertainty resulting from the COVID-19 pandemic, need and ability to obtain future capital, and maintenance of intellectual property rights. Additional information on risks facing Microbot Medical can be found under the heading Risk Factors in Microbot Medicals periodic reports filed with the Securities and Exchange Commission (SEC) and in the prospectus supplement related to the registered direct offering to be filed with the SEC, which are or will be available on the SECs web site at http://www.sec.gov. Microbot Medical disclaims any intent or obligation to update these forward-looking statements, except as required by law.

Investor Contact:

Michael PolyviouEVC Groupmpolyviou@evcgroup.com732-933-2754

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Microbot Medical Appoints the Co-Founder of Corindus Vascular Robotics to its Board of DirectorsVascular Interventions Executive Will Contribute...

25 years of experience and flexible system design make Motion Controls Robotics’ robotic roll handling systems a must see at 2020’s Virtual Converter…

The 2020 Virtual Converters Expo runs from Monday, August 24 - Tuesday, August 25. MCRI representatives will be available from 9am 4pm both days. Each visitor will be able to watch the robot systems in a virtual booth environment, ask questions, and chat with the MCRI team about adding automation. Motion Controls Robotics is also buying lunch for the for the first four visitors that chat about robotics.

Fremont, Ohio August 5, 2020 - Celebrating 25 years of developing quality robotic solutions, Motion Controls Robotics, Inc (MCRI) specializes in systems for the paper, film, foil, and nonwovens companies. Like many live events, the 2020 Converters Expo has selected to go virtual. This allows visitors a chance to still see all the new innovations in converting, discuss current issues, and find the right solution. Tickets for this year's event are free, so take advantage of the this offer to learn and network with people in the converting industry. Register for the event here - https://www.packagingstrategies.com/converters-expo/registration-pricing

Motion Controls Robotics provides automation solutions to the paper, film, foil, and nonwovens industries through applications including:

Roll HandlingRoll LabelingRoll Bagging/PackagingPalletizingCase PackingAutomated Guided Carts

The 2020 Virtual Converters Expo runs from Monday, August 24 - Tuesday, August 25. MCRI representatives will be available from 9am - 4pm both days. Each visitor will be able to watch the robot systems in a virtual booth environment, ask questions, and chat with the MCRI team about adding automation. Motion Controls Robotics is also buying lunch for the for the first four visitors that chat about robotics.

Stop by the Motion Controls Robotics virtual booth to download information and watch roll handling system videos. Then set up a meeting with James Skelding, Director of Sales and Marketing or Earl Raynal, Regional Sales Engineer to discuss a specific robotic roll handling application.

About Motion Controls Robotics - Founded in 1995 and celebrating 25 years of continuous growth, Motion Controls Robotics is a leading provider of automation solutions to manufacturing industries. The company provides full service robotic solutions from concept to installation and service/support that keep manufacturers competitive. Motion Controls Robotics creates solutions for Fortune 500 and small to medium-sized companies. Motion Controls Robotics provides automation solutions to manufacturers, distributors, and warehouses for a variety of applications including material handling (case packing, palletizing and machine tending), and vision-guided systems. Motion Controls Robotics is an exclusive Level 4 Certified Servicing Integrator for FANUC Robotics, and a SmartCart Automatic Guided Cart Value Added Reseller (VAR) for Daifuku Webb. Motion Controls Robotics' northwest Ohio headquarters is located at 1500 Walter Avenue, Fremont, Ohio. http://www.motioncontrolsrobotics.com

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25 years of experience and flexible system design make Motion Controls Robotics' robotic roll handling systems a must see at 2020's Virtual Converter...

Out of this World GM Robotics Come Down to Earth in its Factories – DesignNews

General Motors is applying robotics know-how it developed for NASAs Robonaut on the International Space Station to help its factory workers perform repetitive tasks with less strain.

The RoboGlove was developed from Robonauts technology so successfully that it received NASAs 2020 Innovation of the Year award. The glove provides an electric assist to the wearers grip, squeezing with an additional 15 to 20 lbs. of force. It has the ability to crunch at 50 lbs. of force for short bursts, so there is no jar lid that will defy RoboGloves grip.

Related: Sculpture Becomes 1st Artwork 3D-Printed in Space on ISS

GM workers have tougher tasks than opening jars. GMs director of global manufacturing integration, Dan Grieshaberreports that the companys employees have been using the gloves in both vehicle assembly areas and while assembling components like engines and transmissions.

NASA's Robonaut 2

Related: Factory of the Future Tailored to the Smaller Manufacturer

GM and NASA developed the RoboGlove, but they partnered with Swedens Bioservo Technologies to manufacture and sell the gloves as the IronHand.

The glove has an array of sensors that detect when the wearer is clenching their fingers. The signal from these sensors activates the built-in actuators, which tug on the fingers via steel cables in the same fashion as mechanical bicycle brakes.

Power comes from an external battery pack that the user can wear as a backpack or in a fanny pack. The latter has the benefit of shifting the batterys weight to the users hips rather than to their shoulders and back, Grieshaber explained.

RoboGlove at work in GM's Orion Assembly Plant

The gloves response to the users input is custom-adjustable via a Bluetooth-connected smartphone app that tunes how much force the glove provides each finger.

RoboGlove/IronHand has been a work in progress for a decade, with continuous improvement along the way. As with so many things, software has been a big change, as the gloves programmability is a recent upgrade compared to earlier versions, said Grieshaber.

The internal sensors have gotten smaller, too. That has allowed the glove itself to feel less intrusive on your ability to handle things, he said. From a tactile feel standpoint, the gloves are becoming more natural.

Further, the gloves are made of increasingly durable materials to withstand the strain of continuous factory work. The gloves would literally wear out from use, Greishaber stated. In an assembly plant, youre building 60 vehicles an hour. Over an 8-hour shift theres a lot of wear and tear.

The biggest improvement to the glove has been the decades advancement in battery technology. They have gotten smaller, more powerful, lighter, and they generate less heat, he said. Working in an un-air conditioned factory with a heat-generating battery backpack was a sore point of glove use for wearers, he reported. Factory workers would tell us, I love what it is doing for my hands, but the heat is killing me!

This problem has been mitigated by the newer batteries as well as their relocation to the fanny pack, leaving the users back uncovered.

As RoboGlove matures, it could find its way back to the space station, this time as a tool for the astronauts to wear when their perform service tasks rather than as an appendage on Robonaut.

The benefits include mitigating fatigue, but the spacesuit RoboGlove also provides increased grip strength compared to a non-actuated spacesuit glove. The second-generation design essentially provided power steering of a gloves fingers to reduce the amount of effort, said Jonathan Rogers, deputy chief of the Robotic Systems Technology Branch at Johnson, who served as the project manager for RoboGlove from 2015 to 2017. To use RoboGlove in space, the design must be further matured and tested.

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Out of this World GM Robotics Come Down to Earth in its Factories - DesignNews

COVID fighting technology leader Solaris adds to robotics offering with acquisition of Jetbrain – PRNewswire

Since 2017, Solaris has conducted research on the effectiveness of its pulsed UV technology against communicable human respiratory viruses like novel coronaviruses (COVID-19) with outcomes proving its ability to eradicate +99% of such pathogens in as little as 10 seconds. "COVID has accelerated robotics deployment by five years," said Adam Steinhoff, Co-Founder, and CEO, Solaris. "In continuing our mission to improve the safety of patients and support healthcare workers, we identified Jetbrain's technology as an opportunity to improve upon our core products while providing safety, accountability and compliance-based platform technologies that help our customers effectively utilize resources and improve workflows."

Adds Val Ramanand, Co-Founder and Executive Chairman, Solaris, "At Solaris we are very proud of the growing impact we make on a daily basis in the healthcare industry by delivering practical and approachable products, designed to improve patient outcomes and healthcare operations. The acquisition of Jetbrain supports our continued mission to improve care, keep spaces safe, and ultimately help save lives in healthcare facilities globally."

Jetbrain products include delivery robots that feature a secure and traceable chain of custody for medicines and blood products, as well as patient experience robots that provide anything from clinical support to wayfinding help. The addition of Jetbrain's team enhances Solaris's expertise in healthcare robotics while extending its offering from whole room disinfection to automated delivery, logistics, and ultimately patient experience - thus delivering industry's first ecosystem approach to healthcare robotics.

"With its growing market position and extensive distribution network, Solaris is well-positioned to help us further develop and deploy our technologies while continuing to support our mission of improving healthcare using cutting edge AMR technologies across a broad spectrum of use cases," said Ajay Vishnu, Founder & CEO of Jetbrain Robotics, who assumes the role of CTO in the merged entity.

For more information visit solarislyt.com

Images available on request.

About Solaris Disinfection

Solaris Disinfection has built Lytbot, a portable 'no-touch' disinfection technology that uses pulsed UV light to eliminate pathogens in seconds. Automated disinfection represents a critical component in the future of healthcare infection prevention. Use of automated technologies can dramatically reduce infection rates, protecting lives and healthcare budgets. Learn more at solarislyt.com

About Jetbrain Robotics

Jetbrain Robotics builds robots that make hospitals smarter. End to End Solution for New Age Hospitals to provide enhanced patient care, using Autonomous Mobile Robots (AMR's) that assist with nursing & managing internal logistics, enabling hospital staff to focus on what they do best... Save Lives Learn more at jetbrain.ai

SOURCE Solaris Disinfection Inc.

https://solarislyt.com/

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COVID fighting technology leader Solaris adds to robotics offering with acquisition of Jetbrain - PRNewswire

First-of-its-kind machine brings robotics to copper refining – Northern Ontario Business

Ionic Mechatronics in Sudbury is infusing an old copper-refining technology with new life, increasing safety and efficiency in the process.

Later this month, the firm will roll out an automated copper starter sheet machine that uses robotics in the transfer of all copper material, which the company says is the first of its kind in the world.

Copper starter sheet machines arent new. Built in the 1980s and 1990s, the technology has been used in the purification of copper for decades. But past iterations have relied on a combination of labour and hydraulics to get the job done.

The old machines werent robotic. They were a lot of linear transfers, or a lot more hydraulic systems, explained Ryan Catton, Ionics business development manager.

The ones weve been able to develop now are really removing the people from doing the work.

Copper starter sheet machines use a sheet of impure copper, dipped in a chemical bath to start the process of electrolysis, which purifies the metal.

When the operation is complete, the resulting copper sheets are removed and the process is repeated.

Over the years, as companies started to migrate their systems over to newer technology, copper starter sheet machines fell somewhat out of favour, Catton said.

But the machines were so well built, they last for decades before needing to be replaced, and so many companies still use them.

The company that used to do them got bought out by another company, so there are not very many people that do these, Catton said.

A new starter sheet machine hasnt really been built in years, because these are such rugged and robust machines.

But now, as the equipmentstarts to show its age, Catton said many companies believe the only option is to completely overhaul their existing setup.

Ionics solution allows them to either retrofit existing machinery or build something completely new.

We looked at the need and we've come up with a totally new design for the same process, but using robotics and, really, just putting copper sheets on one side and you're getting your finished product out the other side.

It helps make the job safer by removing employees from that part of the operation, reducing their exposure to toxic substances and gases, while also lowering the risk of musculoskeletal injuries, he added.

After a year in development, the first of these new machines will be ready to be sent to a customer in Arizona, at the heart of the U.S. copper belt, by mid-August.

Ionic has also received interest in the technology from a company in Poland, along with distributors in South Africa and India.

Were also looking at a similar application for a different metal for a starter sheet machine, Catton said. Were going to be able to take the same technology and apply it not only to copper, but to other metals.

This flurry of activity comes as Ionic embarks on an in-house construction project to double the size of its 12,000-square-foot shop in the Sudbury bedroom community of Lively, which will give staff more room to work.

As COVID-19 makes its way around the globe, many operations have stalled, but Catton said Ionic has remained busy over the last several months.

Many larger projects have been shelved as companies trim their capital budgets, but a steady stream of smaller jobs has kept staff working and the shop humming.

Theyre not these million-dollar machines, but being able to do these smaller automation studies or small automation projects has definitely helped out and have kept us busy throughout, Catton said. Its been good.

With pandemic uncertainty continuing, Catton anticipates more companies will look to automation in keeping with social distancing protocols to keep people safe and production running.

We can look at automation and then we can look at how to repurpose the individuals and put them into some tasks where we don't feel like they would be at any risk of any kind of pandemic or disease, or COVID, or whatever it is at that point.

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First-of-its-kind machine brings robotics to copper refining - Northern Ontario Business

COVID-19 Update: Nuclear Robotics Market Competitive Strategies, Regional Analysis Forecast 2025 |Northrop Grumman, IRobot, BAE Systems, AB Precision…

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Market Segment By Type: (Autonomous robot , )Market Segment By Application: (Measurements, Inspections, Radiochemical Handling, Nuclear Decommissioning, Other)

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Regions Covered in the Global Nuclear Robotics Market: The Middle East and Africa (GCC Countries and Egypt) North America (the United States, Mexico, and Canada) South America (Brazil etc.) Europe (Turkey, Germany, Russia UK, Italy, France, etc.) Asia-Pacific (Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)

Years Considered to Estimate the Market Size:History Year: 2015-2019Base Year: 2019Estimated Year: 2020Forecast Year: 2020-2025

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COVID-19 Update: Nuclear Robotics Market Competitive Strategies, Regional Analysis Forecast 2025 |Northrop Grumman, IRobot, BAE Systems, AB Precision...