Category Archives: Robotics

The growth opportunities for AI and robotics in manufacturing are vast and projected to reach $182 billion globally by 2027. Companies that fail to adopt these exponentially advancing technologies as part of their process risk falling behind, as smart factories powered by intelligent machines become the norm.

Artificial intelligence (AI) and robotics are revolutionizing manufacturing, providing scale, speed, and time-to-market advantages. According to the World Economic Forum, over 50% of manufacturers will adopt AI by 2025 as these technologies are proving effective in boosting shop floor efficiency, quality, and flexibility.

AI gives robotics programming and manufacturing platforms unprecedented adaptability, scale and speed. AI and robotics also are the catalysts that enable manufacturers to achieve more in less time and at a lower cost. Automating repetitive, dangerous, or ergonomically taxing manual tasks, including heavy lifting, materials handling, and assembly is just the start of these two technologies many contributions to manufacturing.

Combining artificial intelligence and robotics across shop floors also automates quality inspection, where AI helps reduce defects and scrap. The growth opportunities for AI and robotics in manufacturing are vast and projected to reach $182 billion globally by 2027. Companies that fail to adopt these exponentially advancing technologies as part of their process risk falling behind, as smart factories powered by intelligent machines become the norm.

Integrating Artificial Intelligence and robotics continues to revolutionize manufacturing by providing new automated methods to improve production efficiency and quality while reducing costs. Powered by the data AI and machine learning algorithms produce, robots can now perform complex manual tasks with unmatched precision and speed. This automation provides the accuracy, scale, and speed manufacturers need to stay competitive, meet customer delivery dates, and stay competitive during turbulent economic times. Key applications yielding major benefits include:

Robotic arms with sensors, computer vision, and artificial intelligence can take over heavy lifting, materials handling, assembly, and other repetitive manual work. DELMIA Robotics solutions provides the programming and simulation tools to enable this automation with material-handling robots. This frees the human workforce for higher-value functions and improves safety by reducing ergonomic strains. According to McKinsey, automating predictable physical work could boost global productivity by 0.8 to 1.4% annually.

Orchestrating AI and robotics in combination with manufacturing execution systems (MES) and enterprise resource planning (ERP) systems is defining the future of mass customization and design-for-manufacturing. These technologies enable manufacturers to produce customized products at scale profitably. AI automates repetitive design and production tasks, freeing engineers to focus on delivering faster innovation. DELMIA optimizes robotic routings, work instructions for each unique configuration, and is integral to ensuring mass customization and design-for-manufacturing strategies succeed.

Robotics manufacturing flexibly switches between real-time product variations while ensuring accuracy and precision. AI optimizes production plans and logistics in real time, tailoring them for mass customization. Intelligent design tools use AI to optimize manufacturability. Together, AI and robotics amplify the advantages of integrated design-to-manufacturing platforms, accelerating throughput, quality, and profitability. Manufacturers can now deliver large-scale, small-batch tailored products and capture more revenue opportunities.

DELMIA Robotics optimization leverages AI algorithms to analyze terabytes of manufacturing data, identifying patterns and anomalies for optimizing planning and scheduling in real time. AI-based DELMIA techniques effectively detect and predict potential production constraints and simulate scenarios to minimize downtime and bottlenecks.

Combining DELMIA Robotics AI-based manufacturing intelligence, robotics simulation, and integration with manufacturing execution systems (MES) and enterprise resource planning (ERP) further improves production yield rates and quality consistency across all production centers. When the insights from DELMIAs unified robotics, MES, and ERP data become ingrained, it leads to greater customer satisfaction, repeat sales, and profitability.

Combining IoT, IIoT, and Programmable Logic Controller (PLC) sensors and AI predictive analytics minimizes unplanned downtime of machinery, including robotics across shop floors. Algorithms detect early performance anomalies and predict maintenance needs before failures occur. Instead of rigid schedules, maintenance is performed only when required. According to PwC, AI-enabled predictive maintenance can reduce maintenance costs by 10-40% and decrease overall downtime by 20-50%. In one case, AI helped a rail company cut unplanned downtime by 35%, saving an estimated $50 million. As these examples highlight, predictive maintenance powered by AI delivers major efficiency and cost gains.

DELMIA robotics also helps validate production systems and robot programming within a 3D collaborative environment before building the production system using Virtual Twin techniques and technologies. It can also enable the virtual commissioning of robotics systems to confirm that they work as expected before the control program is downloaded to actual equipment. This can further reduce the risk of failures and optimize the performance of robotics systems. DELMIA robotics is a valuable tool for enhancing predictive maintenance with artificial intelligence in manufacturing.

Robots with computer vision and AI-based deep learning can inspect products for defects autonomously before they leave production centers, reducing the need for return material authorizations (RMAs) to customers. This lowers customer complaints and boosts customer loyalty and trust by catching defective products before shipment. AI-based algorithms learn from the data they capture, analyze, and act on, strengthening the quality muscle memory of production centers using these technologies. McKinsey found that advanced image recognition techniques for visual inspection and fault detection with AI can increase productivity by up to 50%. McKinsey also found that AI-based visual inspection with image recognition can improve defect detection rates by up to 90% compared to human inspection. Moreover, DELMIA Robotics software can help validate and optimize robot programming and simulation in a Virtual Twin 3D collaborative environment before building the production system. This can further enhance the performance and reliability of robots for quality inspection.

Manufacturing is transforming with AI and robotics, which offer scale, speed, and time-to-market advantages. The AI in manufacturing market size will grow from $2.3 billion in 2022 to $23.6 billion by 2030, with a 31.1% CAGR. The industrial robotics market will reach $86.6 billion by 2027, up from $50.3 billion in 2021. These numbers show how AI and robotics play a vital role in manufacturing.

AI and robotics power design-to-manufacturing platforms that optimize complex tasks, increase quality and productivity and streamline customized product development. Intelligent robots work with human workers, improving flexibility, precision, and safety. AI and robotics enable a company with agile manufacturing, which allows mass personalization and on-demand production, meeting customer demand and supply chain dynamics.

AI and robotics make the factories of the future smarter and more efficient. Manufacturers need to use these exponential technologies to gain a competitive advantage. DELMIA Robotics software helps manufacturers validate and optimize robot programming and simulation in a 3D collaborative environment before building the production system. This reduces the risk of failures, saves time and cost, and improves the performance and reliability of robots for various production processes.

Louis Columbus, is senior industry marketing manager at DELMIA. DELMIA empowers manufacturing, supply chain and service providers to efficiently plan, manage, optimize and execute their operations.

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The Interplay Between Robotics and Artificial Intelligence in Manufacturing | RoboticsTomorrow - Robotics Tomorrow

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Doosans PRIME-SERIES P3020 cobot has the longest reach of any of the companys cobots to date. | Source: Doosan Robotics

Doosan Robotics Inc. unveiled its latest and most powerful series of cobots yet: the PRIME-SERIES, or P-SERIES yesterday. Its new P3020 cobot, part of the line, is the companys longest-reaching cobot to date.

The P3020 collaborative robot (cobot) has a payload of up to 30 kg (60 lbs) and a reach of 2,030 mm (80 in). This means it can palletize from the floor to up to 2 m high, stacking up to 10 layers of boxes approximately 8 inches tall, using its simple fixed base without a lift.

As a motion platform company, Doosan Robotics is meeting the ever-growing need for cobots to mimic human motion, powerfully and safely, said William Ryu, CEO of Doosan Robotics. The robotics industry continues to grow at an exponential pace and our lineup of software, cobots and AI differentiates us in our mission to develop cobots with a max-powered, max-efficiency, max-safety mindset.

The South Korean-based cobot manufacturer said its robots can work in several industries, including manufacturing, logistics, food and beverage, architecture, filmmaking, service sectors, and medicine. Its H-SERIES cobot line, released in 2022, has attracted major global customers like Schiphol Airport and Wacker Korea. This has enhanced its global market share by 72%.

Doosans P-SERIES has low power consumption compared to similar payload cobots. It does this by applying its built-in gravity compensation mechanism, inherent wrist-singularity free, and a 5 degree-of-freedom movement with the 4th axis removed and 6th axis speed increased to 360 degrees/second.

The robot has also achieved the highest PL (e) and Cat 4 safety ratings to ensure both a max-powered and max-safety experience for users.

Doosan says its systems can adeptly maneuver through intricate scenarios while infusing tasks with enhanced efficiency, safety, and ingenuity. The AI systems behind the cobots have continuous learning capabilities and update its model by autonomously downloading required modules for smooth integration.

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Earlier this year, Doosan released two new products: its new Dart-Suite software and Otto Matic palletizing system. The company said the artificial intelligence powering its systems continuously learns and updates its model by downloading modules automatically.

Doosan described Dart-Suite as a robot ecosystem that redefines its customers experience with its robots and makes automation more accessible. The platform incorporates AI to enable users to develop, sell, download, and trigger actions through various interfaces. The suite uses an integrated development environment (IDE), which Doosan said allows customers to create modules tailored to their needs, similar to mobile device apps.

Otto Matic is a depalletizing and palletizing system that can handle unstructured and random-sized boxes. Doosan said it developed the system to bring additional deep learning and computer vision technology to its cobots.

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Doosan Robotics releases its longest reach cobots with PRIME SERIES - Robot Report

Summary

The company collaboration scales supply chain for FoxBot ATL andestablishes a nationwide service and support network for Autonomous Forklifts.

SUMMERVILLE, S.C. and AUSTIN, Texas - May 7, 2024 -KION North America(KION NA), manufacturer of Linde Material Handling equipment, andFox Roboticshave entered into a non-exclusive partnership wherein KION NA will manufacture and assemble FoxBot autonomous trailer loader/unloaders (ATLs) at its facilities in Summerville, South Carolina. We are at a pivotal moment in the logistics and transportation industry, where innovation is key to addressing some of the most pressing challenges we face. Specifically, in the realm of automated trailer loading and unloading, the last remaining piece of the end-to-end warehouse automation puzzle, Fox Robotics stands out by far as the dominant leader with the most robust AI/ML algorithms, tech stack, and deployed robot fleet weve ever seen, comments Jonathan Dawley, President and CEO at KION North America. We are delighted to announce our collaboration with Fox Robotics to launch this groundbreaking product in the U.S. market. This partnership signifies a major leap forward in our commitment to enhancing efficiency, safety, and reliability in our customers' operations. "Fox Robotics is scaling and expanding its supply chain capabilities significantly via the partnership with KION North America," said Marin Tchakarov, CEO and President at Fox Robotics. "Our traction in the marketplace is tremendous, and Fox Robotics is at an inflection point in its growth arc. We are experiencing unprecedented demand and have a massive list of bookings for Fox Robotics products and solutions. The partnership with KION NA will most certainly pave the way to capture all this commercial growth." TheFoxBot autonomous forkliftis the world's first Class 1 electric, stand-up autonomous forklift designed for load/unload operations on warehouse loading docks. Classified as an autonomous mobile robot (AMR), the FoxBot robotic forklift automates various operator tasks to improve workplace safety, increase productivity, and enhance employee satisfaction. The company started selling ATLs commercially in 2019 and is the first mover in the category. Recently, Fox Robotics announced that its installed base of FoxBot ATLs has processed nearly 3 million pallet pulls to date. "Thelogistics space is the single biggest market for automation for the next ten years. Converting the shipping and receiving dock, the gateway to the warehouse, from a manual operation to an automated one will drive the greatest growth and change,"said Till Reuter, board director for Fox Robotics and former CEO of Kuka Robotics. "Fox Robotics is poised to capture this growth in automation as the dominant leader in this space and the first one to deliver on the promise of true end-to-end automation of the warehouse of the future."

Headquartered in Summerville, S.C.,KION North America Corporationis a member of the KION Group, one of the world's leading manufacturers of industrial trucks. Their brand companies, Linde and Baoli, serve the specific industrial truck requirements of the US, Canadian, and Mexican markets with a broad and complementary product portfolio. KION North America produces material handling equipment known for its innovative technologies, reduced energy consumption, and low operating costs. KION North America also works closely with its sister company, Dematic, a global leader in automated material handling that provides a broad range of intelligent supply chain and automation solutions.

Founded in 2017, Fox Robotics is leading the industry in autonomous pallet workflows to improve workplace safety and productivity in warehouses across the U.S. and Canada. The company develops, manufactures, and sells the world's first autonomous trailer loader/unloader, the FoxBot. Fox Robotics is backed by investments from BMW i Ventures, Menlo Ventures, and Zebra Technologies Corp.

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KION North America and Fox Robotics Announce Non-Exclusive Strategic Partnership - Automation.com

A robot constructed by the Mars Robotics Association. Butler Eagle file photo

On Saturday, May 11, the public can visit Mars to experience the thrill of controlling a rover on the surface of Mars.

The Mars Robotics Association is hosting an event which will give the public a chance to control robots not too dissimilar to NASAs Perseverance rover, which currently is scanning the Red Planet for signs of life.

Were trying to simulate the same principles as the real rovers, said Jeff Beckstead, president of the Mars Robotics Association.

On Saturday, visitors can drive these robots across an 8-by-16-foot surface representing a portion of Mars, with an image taken from a real-life satellite capture of the planet. The robots were constructed of Lego bricks by members of the Mars Robotics Association.

These robot pilots are tasked with collecting rock samples and determining whether the samples are worthy of being investigated for signs of life.

Each one has a test tube thats inserted into it, and inside that test tube is a color that would represent that type of rock, Beckstead said. We go out, find rocks, then we bring them back to base. Then, we evaluate those to see if theyre valuable or not.

In so doing, they will simulate the Perseverance rovers mission to collect rocks to study for signs of life on Mars.

The Perseverance rover is collecting rock samples on Mars and putting them in sample tubes, Beckstead said. The next mission to Mars will bring those samples back to Earth for laboratory investigation.

Saturdays event is a collaboration between the Mars Robotics Association and NASAs Jet Propulsion Laboratory and also is part of Remake Learning Days, which is taking place across southwestern Pennsylvania through May 22. Remake Learning, a nonprofit educational network, provided the grant for this event.

Theyve been promoting a lot of different activities across the state that are focused on STEM education, Beckstead said. Mars Robotics was awarded a grant to help us support this activity.

The event will take place from 11 a.m. to 3 p.m. at the Mars municipal building, 301 Arch St. According to the events webpage, the event is targeted mainly at those ages 8 to 18.

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Mars Robotics offers chance to drive Mars rover on Saturday - Butler Eagle

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The group with the robot tutor made fewer errors and spoke more fluently than the group with human tutors, indicating the effectiveness of robot-assisted learning.

Credit: Takamasa Iio from Doshisha University Image Link: https://media.springernature.com/lw685/springer-static/image/art%3A10.1007%2Fs12369-024-01134-0/MediaObjects/12369_2024_1134_Fig1_HTML.jpg?as=webp

Advancements in large language models, robotics, and software such as text-to-speech, have made it possible to develop robots that can understand language, interact physically, and communicate verbally. These breakthroughs have opened up possibilities for robots to be used for educational purposes. However, this raises the question of whether robots are as good as human tutors. While robots offer certain benefits, they cannot replicate the nuanced interactions and personalized feedback human tutors provide.

To determine the suitability of using robots for education, Associate Professor Takamasa Iio from Doshisha University, along with Associate Professor Yuichiro Yoshikawa, Professor Hiroshi Ishiguro from Osaka University, and Associate Professor Kohei Ogawa from Nagoya University, Japan, compared the performance of current Robot-Assisted Language Learning (RALL) systems to human tutors. Their study published in the journal International Journal of Social Robotics on April 11, 2024, explored the effectiveness of each approach in improving students' English-speaking skills in second language learning. There has been an active movement to utilize robots in education, particularly in language education, which requires communication. However, it was not clear what benefits there would be in utilizing robots. We began this study with the belief that in order to expand the use of robots in the future, it would be necessary to compare the discussion with the baseline of human tutors, says Dr. Iio.

The researchers conducted an experiment involving 26 university students whose native language is Japanese. The students underwent a pre-test for an initial assessment of their English-speaking skills. Based on the average scores, the students were divided into two groups: 14 students received instruction from a robot, while the remaining 12 participants received online lessons from English language teachers. Over the course of seven days, both groups engaged in daily 30-minute sessions aimed at improving their English-speaking skills. The robot used was a table-top humanoid called CommU, which students could interact with using a tablet. This robot model could display human-like behaviors. It could nod to agree, slump to show thoughtfulness, and raise its hands to express joy or surprise.

In addition, there were three speaking exercises. The first involved roleplay, where the tutor (human or robot) and the student enacted a conversation in specific situations. The students listened to their scripts from the tutor and then repeated them. In the case of the robot, an audio file containing the speech of a native speaker was played instead of text-to-speech. The second exercise was flashcard practice, where students listened to their tutor deliver the script and repeated it to memorize it. In the final exercise, the students reenacted the conversation with their tutor using the memorized scripts. On the last day, participants underwent tests to assess their speaking errors, fluency, pronunciation, and speech complexity (number of words used in sentences).

All participants underwent a pre-test on the first day, followed by 30 minutes of daily study for 7 days, and three post-tests on the final day. The result indicated that the group taught by the robot made fewer errors and spoke more fluently than the group taught by human tutors. However, no significant difference was observed in outcomes between robots and human tutors for other aspects. The researchers believe that the improvement is because the students could practice the exercises with the robots much more than they could with the human tutor. This level of repetition improved their memory retention and speaking proficiency.Additionally, the expression of the robot may have reduced anxiety, allowing them to speak English without fear of judgment.

Social robots could be used more in second language learning. They are likely to play an active role in repetitive practice aimed at consolidating basic words, phrases, and grammatical structures in memory, highlights Dr. Iio.

While current RALL systems are sufficient to provide basic English training, the researchers predict that future systems will become more advanced.They may be able to recognize non-native speakers speech, offer corrections, and conduct interactive lessons and open-ended dialogues. However, since the fundamental purpose of language is communication with others, human tutors will remain essential for helping learners feel more comfortable and confident when using a new language in real-life situations.

About Associate Professor Takamasa Iio from Doshisha University, Japan Dr. Takamasa Iio received the Ph.D. degree from Doshisha University, Kyoto, Japan, in 2012. He has worked at ATR, Osaka University, and the University of Tsukuba. Currently, he is an associate professor at Doshisha University, Kyoto, Japan. His field of expertise is social robotics. He explores the impact of human-robot interaction on cognition and behavior, alongside societal shifts. His current research focuses on social robots that can enhance social capital in human society by mediating relationships between people.

Funding information This work was supported by JST Moonshot R&D Grant Number JPMJMS2011 (Analysis), JSPS KAKENHI Grant Number 19H05691 (Development of the robot system and the tablet interface), and the Benesse Corporation (Development of the learning materials and assessment of the tests).

Media contact: Organization for Research Initiatives & Development Doshisha University Kyotanabe, Kyoto 610-0394, JAPAN E-mailjt-ura@mail.doshisha.ac.jp

International Journal of Social Robotics

Observational study

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Comparison of Outcomes Between Robot-Assisted Language Learning System and Human Tutors: Focusing on Speaking Ability

11-Apr-2024

The authors declare that they have no conflict of interest.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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Comparative analysis of robot-assisted language learning systems and human tutors in English conversation lessons - EurekAlert

The Shadow Hand robotic device was built to withstand collision damage

Shadow Robot Company

A new robot hand provides extremely fast and flexible finger movements, while also being tough enough to survive intense damage. That durability helps the hand, which is already being used in Google DeepMinds robotics experiments, during the trial-and-error learning required to train artificial intelligence.

This latest robotic hand developed by the UK-based Shadow Robot Company can go from fully open to closed within 500 milliseconds and perform a fingertip pinch with up to 10 newtons of force. It can also withstand repeated punishment such as pistons punching the fingers from multiple angles or a person smashing the device with a hammer.

The new hands robust design is well suited for AI-powered robotics experiments based on reinforcement learning, which allows robots to gradually learn how to interact with environments by fumbling through tasks using trial and error, says Ram Ramamoorthy at the University of Edinburgh in the UK.

Any interaction with the world is a collision damage risk, said Rich Walker, director of the Shadow Robot Company, during a press conference.

One trade-off is that the hand is heavier than some other options because the design decisions are aimed at reliability over long-term usage, says Ramamoorthy. The new Shadow Hands chunky, three-fingered set-up weighs 4.1 kilograms in total and 1.2 kilograms per finger.

This structure makes the hand look much less anthropomorphic than some other robotic limbs, but also makes it more versatile: it can be modified with more fingers if needed, and each finger is a modular component that can be swiftly swapped out for a replacement in case of damage.

Each robotic finger has hundreds of sensors on its fingertips and dozens on the other finger segments. Tiny cameras focus on the inside surface of each robotic fingers silicone skin touching an object may deform the robotic skin, and this interior view can thus indicate the objects hardness and shape.

Its excellent in terms of sensing, and its super robust, says Ingmar Posner at the University of Oxford. Its also engineered to be easily fixable.

Some research labs and companies beyond Google DeepMind may find the capable hand to be useful, says Posner. But it is likely to be expensive Shadow Robot Company has not yet announced its price and other researchers may prefer cheaper robotic hand options, even if they lack some or all of the sophisticated sensing and object-handling capabilities that the Shadow Hand combines in one package.

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DeepMind is experimenting with a nearly indestructible robot hand - New Scientist

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Nvidia and Alphabets Intrinsic have teamed up to show off advancements in robotic grasping and industrial scalability.

The companies said that the landscape of robotics will further change with the integration of new AI and platform technologies. At the Automate trade show in Chicago this week, Intrinsic is unveiling advances in robotic grasping and industrial scalability, powered by Nvidias Isaac Manipulator and AI capabilities.

Isaac Manipulator, introduced by Nvidia at GTC 2024 in March, represents a milestone in industrial automation. It comprises foundation models and GPU-accelerated libraries designed to facilitate scalable and repeatable workflows for dynamic manipulation tasks. These foundation models, based on transformer deep learning architecture, enable robots to perceive and make decisions autonomously, akin to human-like understanding.

The collaboration between Nvidia and Intrinsic demonstrates the potential for a universally applicable robotic-grasping skill to work seamlessly across various grippers, environments, and objects. Wendy Tan White, CEO of Intrinsic, highlighted the transformative impact of foundation models in simplifying processing challenges, reducing development costs, and enhancing flexibility for end-users.

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For the broader industry, our work with Nvidia shows how foundation models can have a profound impact, including making todays processing challenges easier to manage at scale, creating previously infeasible applications, reducing development costs, and increasing flexibility for end users, Tan White said in a statement.

(Tan White will deliver a keynote address at Automate about what the rise of AI means for innovation and growth, on Friday, May 9, at 9 a.m. CT.)

The development of better robot grip is a central focus of this partnership. Grasping, a coveted skill in robotics, has historically been challenging to program and scale efficiently. However, with the integration of Nvidia Isaac Sim on the Omniverse platform, Intrinsic has leveraged simulation to generate synthetic data for vacuum grasping, paving the way for significant advancements in industrial automation.

The prototype uses Intrinsic Flowstate, a developer environment for AI-based robotics solutions, for visualizing processes, associated perception and motion planning. With a workflow that includes Isaac Manipulator, one can generate grasp poses and CUDA-accelerated robot motions, which can first be evaluated in simulation with Isaac Sim a cost-saving step before deployment in the real world with the Intrinsic platform.

Nvidia and Intrinsic aim to bring state-of-the-art dexterity and modular AI capabilities to robotic arms, offering a comprehensive collection of foundation models and GPU-accelerated libraries to accelerate new robotics and automation tasks.

On Tuesday, May 7, Nvidia senior research scientist Adithya Murali and Intrinsic chief science officer Torsten Kroeger will demonstrate the companies collaborative efforts in the session Automating Smart Pick-and-Place With Intrinsic Flowstate and NVIDIA Isaac Manipulator at Automate.

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Nvidia and Alphabet's Intrinsic aim to revolutionize next-gen robotics - VentureBeat

Summary

Modern retailers have an incredible opportunity to futureproof their warehouse operations today, with the goal of increasing efficiency to meet this surging consumer demand.

Revenue related to e-commerce will grow nearly 10% YoY between now and 2029, at which point global revenue for e-commerce alone will reach nearly $5 billion yearly. As a frame of reference, thats more than double the e-commerce sales numbers from 2020. Modern retailers have an incredible opportunity to futureproof their warehouse operations today, with the goal of increasing efficiency to meet this surging consumer demand. However, if they dont take action, these same retailers risk labor shortages, increasing labor costs and ultimately falling behind in meeting customer expectations, which will lead to massive losses in market opportunities for their more adept competitors. As they stare down the challenge of growing demand and extended labor shortages, I urge warehouse managers to educate themselves on the benefits of efficient solutions like automation and robotics.

The pandemic and modern consumer behaviors have exposed deep cracks in traditional warehouse operations. E-commerce demand is increasing with no indication of stoppage. Expectations surrounding always-on availability for retail distribution have led many warehouses to improve their efficiency to keep pace with demand. For example, over one-fourth of customers have abandoned their carts because they werent offered free two-day shipping. Satisfying consumers appetite for fast, free shipping requires a well-oiled logistics operation. Simultaneously, most retailers face a massive barrier to success: labor shortages. In 2023, nearly eight in ten industrial business leaders cited notable labor shortages as a recurrent issue in their facilities. Robotic automation has become a powerful method to alleviate the pressing issues of decreasing labor and increasing demand. In fact, many retailers already involve AI-powered and 3D vision-enabled robots in their packing and shipping processes. Automation of this caliber increases outcomes like delivery timelines because robots can safely work 24/7, meeting new consumer demand night and day. Furthermore, retailers who adopt the right robotics model will seldom need to service their robotic co-workers outside of routine maintenance.

The right robotics solution will differ from operation to operation. Furthermore, certain warehouses will attain ROI from automation faster than others. Leaders evaluating automation and robotics in their warehouse should consider the following. 1. Your workflow is unique. Automation should acknowledge that fact, not ignore it. Historically, warehouses have been structured around bipedal, two-armed human workers. These workflows dont always benefit AI-powered robots, which come in various sizes and configurations. Thus, most warehouses must be optimized to compensate for new robotic workflows. Robotic solution providers can walk you through a workflow audit process to ensure optimal robot deployment efficiency. During this process, youll identify the areas and processes where automation can bring value. You may also determine that certain older warehouses wont benefit from automation without additional investment, whereas newer spaces may be perfect for employing robotic co-workers. 2. Long-term ROI should outweigh short-term investments. Sticker shock shouldnt be a reason to delay necessary investments into warehouse automation. If youre grappling with the cost of robotics deployment, consider more scalable models like robotics as a service (RaaS), which enable warehouses to deploy robots without owning the steep cost of regular maintenance. Additionally, if youre experiencing friction when attempting to garner buy-in, consider contextualizing the long-term ROI of automation. This includes labor savings, increased productivity and reduced error rates. Companies have reduced their fulfillment costs by up to 50% after introducing warehouse automation. 3. Certain robots can deploy on day 1but only with the right provider. Some robotics providers enable warehouses to realize ROI on day 1however, only if (1) your warehouse is outfitted for automation and (2) software integration is seamless. I advise seeking providers that integrate within existing warehouse management systems (WMS) and/or existing warehouse control systems (WCS). 4. Not all warehouses will benefit from automation today, and thats OK. Because generalized AI on the warehouse floor remains highly conceptual, practical AI-powered robots are purpose-built for specific tasks. The most common examples in logistics are induction, order picking and de-palletization robots. Albeit generally dextrous and capable, these robots will likely perform better on certain items and tasks than others. For example, operations dealing in incredibly delicate, highly variable or temperature-controlled items may not benefit from a modern robotic automation system. However, robotics providers are making strides in this arena by providing expanded gripper strength and analysis capabilities. I advise that leaders in more specialized industries keep their eyes on these emerging technologies. 5. Humans will never become obsolete in warehouse operations. AI robots on the factory floor will change manufacturing labor models, but only in that extended labor shortages will no longer prohibit factories from hitting their revenue goals. Additionally, current employees must learn new skills to adapt to AI robotics workflows. AI-empowered robots are generally autonomous but not infallible. Imagine an unexpected but common induction mishapfor example, a package ripping open on a conveyor belt. Warehouse robots have been trained on how to react in this situation, but different environmental contexts can complicate otherwise simple decisions. Humans become critical during these events. Remote factory workers with access to a robots live feed can pinpoint the item or situation and provide context enabling the robot to make the most advantageous decision. In some instances, that might mean advising the robot to remove and discard the affected item; in other situations, to replace it. By owning high-level decisions like this, humans help factory operations to remain smooth and incredibly efficient.

As e-commerce demand and expectations continue to fluctuate, retailers and warehouse operators must embrace automation and AI-based solutions. However, they must also acknowledge that automation is never a one-size-fits-all solution. By carefully considering factors such as workflow analysis, long-term ROI, software integration and the suitability of specific robotic solutions, retailers can make informed decisions and drive critical efficiencies on the warehouse floor.

With more than 30 years in the robotics and automation industries, Crystal Parrott, COO of Plus One Robotics, has a history of bringing emerging technologies to market. Previously, Crystal served as the Vice President of the Robotics Center of Excellence for Dematic Corp, where she led all robotic initiatives and guided and supported the generation of robotic solution sales in the logistic market. Prior to joining Dematic in 2018, Crystal spent 11 years leading the development of advanced robotics technology and promoting it to create new businesses at Southwest Research Institute. Crystal holds a Master of Science in Management of Technology from the University of Texas at San Antonio as well as a Bachelor of Science in Electrical Engineering from Kettering University.

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Five Things to Consider Before Adopting Robotics for Warehouse Automation - Automation.com

KENDALLVILLE Sir Camelot, a robot designed, built and operated by East Noble High Schools First Robotics Team 8103, showed off its capabilities in a May 3 demonstration at the Community Learning Center for local business and industry leaders.

First Robotics Competition teams design, program and build industrial-size robots according to a strict set of rules and limited time and resources in a real-world engineering project.

Knight Team 8103 members are Benjamin Barker, Braden Golsnerry. Eduarado Gonzalez, Zackery Leichty, Anabel Martin, Bryce Millhouse, Mason Monahan, Jared Price, Kian Ross, Reese Rouch, Joseph Savage, Owen Tackett, Sean Valles, Gunner Willey, Warren Ritchie, Carter McKinley and Ailey Odem.

Mentors are Collin Haynes and Tucker Martin. The team is coached by Shawn Kimmel, the Project Lead The Way engineering and physics teacher at East Noble High School, and Jo Smith, the East Noble Middle School Teacher of the Year.

Sir Camelot is named after one of King Arthurs Knights of the Round Table. The student team members had to design, fabricate and build the robot from scratch to compete in several robotics competitions. The robot is about 3 feet square, very heavy, and designed to pick up a hoop from the floor and launch it toward the target.

The Knight 8103 team painted Sir Camelot in East Nobles blue and gold school colors to make it stand out on the competition floor.

Sir Camelot performed well this season. Team 8103 finished in third place at the Mishawaka Competition with a state ranking of fifth. At the Columbus Competition, the team finished in 10th place with a state ranking of 17th.

Sir Camelot had its best performance at the Indiana state competition, with the team finishing in fifth place with a state ranking of 14th.

Team members put together a highlight video and slide show to open the demonstration. Team coach Kimmel said the Knight robotics program started in 2020 with a budget of $9,000, which had to cover the cost of the robot, competition fees and lodging for the team.

We had six in the first class and we had no experience, Kimmel said.

The team, participated in a video competition in 2021 during the pandemic. By 2023, all of the original team members had graduated.

In the years since, Kimmel said the team has improved with more experience and more guidance from former team members, now in college, returning to mentor the current team members. The team absorbed knowledge by talking with others, and are now viewed as true state competitors who are sought out by other teams for mentoring.

Its an all-new group of students in 2024. Kimmel said robotics has guided students into thinking about careers in engineering. This years senior members are considering Trine University, Marian University Rose-Hulman Institute and Southern Indiana University as places to further their education.

Robots can cost as much as $10,000 to $15,000. Team members have to learn coding to program the robot, and fabricate or order parts for the design-and-build. They learn to design and assemble the electrical system and use impact and other tools

Team 8103s future goals include forming a second robotics team and increasing the program budget to $50,000 through donations, more sponsorships and fundraising. The program also needs new computers. East Noble School Corporation is providing a second classroom to expand the robotics program but does not provide any funding.

Donations are gratefully accepted for the program, and sponsors are welcome. A golf outing on Saturday, Aug 31, at Noble Hawk Golf Links will help the robotics program raise funds for its budget. Sponsorship levels for the outing are: Blue Knight, $1,000; Gold Knight, $550; Black Knight, $450; and White Knight, $150.

Each sponsorship level includes the registration for a team of four golfers for 18 holes, and recognition in several ways. Contact Kimmel at skimmel@eastnoble.net for sponsorship information or golf outing registration form.

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EN robotics team demonstrates real-world learning | News Sun | kpcnews.com - KPCnews.com

Summary

Intrinsic, a software and AI robotics company at Alphabet, has integrated NVIDIA AI and Isaac platform technologies to advance the complex field of autonomous robotic manipulation.

Intrinsic, a software and AI robotics company at Alphabet, has integrated NVIDIA AI and Isaac platform technologies to advance the complex field of autonomous robotic manipulation.

This week at the Automate trade show, in Chicago, Intrinsic is spotlighting leaps in robotic grasping and industrial scalability assisted by foundation models enabled by NVIDIA Isaac Manipulator, unlocking new value in industrial automation with AI.

NVIDIAunveiled Isaac Manipulatorat GTC in March.Isaac Manipulatoris a collection of foundation models and modular GPU-accelerated libraries that help industrial automation companies build scalable and repeatable workflows for dynamic manipulation tasks by accelerating AI model training and task reprogramming.

Foundation modelsare based on atransformerdeep learning architecture that allows a neural network to learn by tracking relationships in data. Theyre generally trained on huge datasets and can be used to process and understand sensor and robot information as magically as ChatGPT for text. This enables robot perception and decision-making like never before and provides zero-shot learningthe ability to perform tasks without prior examples.

NVIDIAs collaboration with Intrinsic, a leading robotics software and AI company, demonstrates the potential for a universally applicable robotic-grasping skill to work across grippers, environments and objects.

For the broader industry, our work with NVIDIA shows how foundation models can have a profound impact, including making todays processing challenges easier to manage at scale, creating previously infeasible applications, reducing development costs, and increasing flexibility for end users, said Wendy Tan White, CEO at Intrinsic,in a blog postannouncing the collaboration with NVIDIA. (White will deliver a keynote address at Automate about what the rise of AI means for innovation and growth, on Thursday, May 9, at 7 a.m. PT.)

Grasping has been a long sought after robotics skill. So far its been time-consuming, expensive to program and difficult to scale. As a result, many repetitive pick-and-place conditions havent been seamlessly handled to date by robots.

Simulation is changing that. EnlistingNVIDIA Isaac Simon theNVIDIA Omniverseplatform, Intrinsic generatedsynthetic datafor vacuum grasping using computer-aided design models of sheet metal and suction grippers. This allowed Intrinsic to create a prototype for its customerTrumpf Machine Tools, a leading maker of industrial machine tools.

The prototype uses IntrinsicFlowstate, a developer environment for AI-based robotics solutions, for visualizing processes, associated perception and motion planning. With a workflow that includes Isaac Manipulator, one can generate grasp poses and CUDA-accelerated robot motions, which can first be evaluated in simulation with Isaac Sima cost-saving stepbefore deployment in the real world with the Intrinsic platform.

Under the collaboration, NVIDIA and Intrinsic plan to bring state-of-the-art dexterity and modular AI capabilities for robotic arms, with a robust collection of foundation models and GPU-accelerated libraries to accelerate a greater number of new robotics and automation tasks.

On Tuesday, May 7, at 11 a.m. CT, NVIDIA Senior Research Scientist Adithya Murali and Intrinsic Chief Science Officer Torsten Kroeger will demonstrate the companies work in the session Automating Smart Pick-and-Place With Intrinsic Flowstate and NVIDIA Isaac Manipulator in the Intrinsic booth 2808 at Automate.Joinourspeaking sessionsat Automate

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NVIDIA and Alphabet's Intrinsic Put Next-Gen Robotics Within Grasp - Automation.com