Daily Archives: July 2, 2023

Excerpted from The Datapreneurs courtesy of Peakpoint Press, an imprint of Skyhorse Publishing.

When artificial general intelligence (AGI), the ability of machines to match or even surpass human intelligence, seems to be within our grasp, we must encode ethics models within our future intelligent machines to ensure they contribute to the betterment of humanity and fulfill the new social contract we need.

While growing up in suburban Michigan, I was the nerdy sort of kid who loved math and science and, not surprisingly, became the AV guy who ran the projector at school. I loved tinkering with electronic gadgets. My other great love as a teenager was science fiction, particularly the work of Isaac Asimov. I read hundreds of his novels and short stories during my teens and twenties. It was not until recently that I began thinking more deeply about intelligent machines ethical and moral implications. I looked back at what Asimov had written about the relationship between people and robots. In addition to featuring robots prominently in his novels and stories, he wrote dozens of essays about them. Asimov concluded they should be respected, not feared or controlled. He developed rules for how they should interact with humanity. Asimov was an optimist and a realist.

I am an optimist and a realist, too. To achieve a future where artificial intelligence benefits humanity, we need a new social contract that governs the relationship between people and the emerging generation of AGI machines.

The concept of a social contract emerged in the Age of Enlightenment, the period of rigorous scientific, political, and philosophical questing that spanned the 18th century in Europe. Traditionally, a social contract is an implicit or explicit deal between the government and the people in a country where individuals surrender some of their freedoms and follow the rules laid out by governments in exchange for other benefits and maintenance of the social order. Because social orders are under constant stress, the values, laws, and regulations that embody social contracts require reexamination and modification when new factors come into play.

The new social contract I have in mind would govern the relationship between people and smart machines assuring that people are safe and the newly emerging AGI entities align with our values and interests. It would consist of a set of rules agreed to by the worlds governments, businesses, and other institutions defining what intelligent machines can and cannot do and how people can and cannot use them.

When I look ahead, I see amazing things coming. We are at the beginning of an intelligence revolution similar to our world in the 1850s during the Industrial Revolution.

This computer science journey began in earnest in the 1940s and 1950s. It was not until the 1960s that universities began offering computer science degrees. Then, the PC, the web, the smartphone, big data, the cloud, foundation models, and tremendous advances in artificial intelligence came in rapid succession. The science and industry that emerged from the IT revolution are still changing rapidly but are also maturing. Technology transforms our world, businesses, and our personal lives.

Now we are on the verge of another great lift. By harnessing AI and other techniques to master the explosion of data we see today, we can understand how the world works much more accurately and comprehensively. We can make better decisions and use Earths resources more responsibly. Throughout my career, I have focused on bringing technology to bear to help businesses succeed. As computer technology developed, its potential impact for good or potential harm increased. I am hopeful these coming technological advances will improve the well-being of our species and the sustainability of life on this planet.

Over the past 80 years of the computing revolution, intelligent machines matched or bested one human capability after another. First, we created machines with expertise in a single domain. With the arrival of foundation models, the depth of AI systems knowledge, the speed with which they react or predict, and the accuracy of their predictions are pretty darned impressive. They already demonstrate a recall of knowledge far beyond human capabilities. Now, we create machines with expertise in multiple domains. These large-scale machine learning models will dramatically lower the cost of intelligence, enabling new smarts and capabilities in applications and services of all types.

I believe machines will possess artificial general intelligence within the next decade.

I see the 2030s and beyond as the golden era of robotics. Todays robots that make cars on assembly lines and clean up nuclear power plants after meltdowns are impressive. But the robots of the future will impress on another order of magnitude. They will be largely autonomous because they cannot always take orders from computing systems located in the cloud. To make machines capable of autonomy, we will have to provide them with AI capabilities that are miniaturized and localized. Initially, these machines will serve single purposes like cleaning our floors, delivering packages, driving vehicles, and flying us around. Over time, more general purpose robots that take on human characteristics and form will emerge.

I believe machines will possess artificial general intelligence within the next decade. It is only a matter of when. These prospects do not frighten me, but they do concern me. What is the societal impact in a world where smart machines are general purpose, matching the capabilities of people and exceeding them in many ways? What ethics and rules will control these machines? In the future, it seems likely that robots will be capable of performing most physical tasks, and intelligent models within them will be capable of performing most intellectual tasks. What will people do if machines and AI systems do all that work?

I am not an expert in AI, and I am not an ethicist. I am an engineer and a businessman. I do not have a clear answer to these issues. These questions will likely be among societys most critical policy issues in the decades ahead. Computer scientists, business leaders, government officials, academics, ethicists, and theologians must work together.

I believe people will develop solutions to the profound ethical issues raised by tomorrows robots and intelligent machines, but I think the process will be messy. In history, every major technological advance has been used, for good and bad. Ultimately, though, common sense prevails, and society establishes laws and regulations that oversee the use of technology. This governance applies to everything from electricity to nuclear technology, and I believe the same will happen with intelligent machines.

We can and will overcome these challenges, and the rising tide can lift all boats. But these issues will not solve themselves. We must think deeply about them and design solutions before the disruptions take full force.

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We need a new social contract for the coming golden age of robotics - Big Think

The global transition to renewable energy sources is rapidly gaining momentum, with solar power playing a crucial role in the shift towards a more sustainable future. As the adoption of solar panels continues to grow, the need for efficient and cost-effective maintenance of these installations has become increasingly important. One of the most promising solutions to this challenge lies at the intersection of autonomous robotics and solar panel cleaning technologies.

Solar panels are highly dependent on their ability to absorb sunlight, and even a thin layer of dust or dirt can significantly reduce their efficiency. According to the National Renewable Energy Laboratory, dirty solar panels can lose up to 25% of their energy output, which translates to a considerable loss in potential revenue for solar farm operators. To maintain optimal performance, solar panels need to be cleaned regularly, which can be a labor-intensive and costly process, especially for large-scale installations.

This is where autonomous robotics come into play. By combining advanced robotics with innovative cleaning technologies, it is now possible to create automated systems that can efficiently clean solar panels without the need for human intervention. These robotic solutions not only save time and labor costs but also minimize the risk of damage to the panels and reduce water consumption, making them an environmentally friendly option.

One of the key factors driving the synergy between autonomous robotics and solar panel cleaning technologies is the rapid advancement in artificial intelligence (AI) and machine learning. These technologies enable robots to navigate complex environments, recognize patterns, and make decisions based on real-time data. In the context of solar panel cleaning, AI-powered robots can analyze the level of dirt on the panels, determine the most efficient cleaning method, and adapt their movements to the specific layout of the solar farm.

Another important aspect of this synergy is the development of specialized cleaning tools and techniques designed specifically for solar panels. Traditional cleaning methods, such as pressure washing or manual scrubbing, can cause damage to the delicate solar cells and are not always effective in removing stubborn dirt and grime. Robotic cleaning systems, on the other hand, can be equipped with advanced technologies such as electrostatic cleaning, ultrasonic cleaning, or even laser cleaning, which can remove dirt and dust without causing any harm to the panels.

The integration of autonomous robotics and solar panel cleaning technologies is already showing promising results in the field. Companies like Ecoppia, a leading provider of robotic solar panel cleaning solutions, have developed fully autonomous systems that can clean large-scale solar installations with minimal water usage and without the need for human intervention. These systems have been deployed in solar farms around the world, demonstrating their effectiveness in maintaining the performance of solar panels and reducing operational costs.

As the demand for clean energy continues to grow, the need for efficient and sustainable maintenance solutions for solar installations will become even more critical. The intersection of autonomous robotics and solar panel cleaning technologies offers a promising path forward, enabling solar farm operators to maximize the performance of their assets while minimizing environmental impact and operational costs.

In conclusion, the synergy between autonomous robotics and solar panel cleaning technologies is poised to revolutionize the way solar installations are maintained, ensuring that they continue to deliver clean, renewable energy for years to come. As AI and machine learning continue to advance, we can expect even more sophisticated robotic solutions to emerge, further enhancing the efficiency and sustainability of solar power generation.

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The Intersection of Autonomous Robotics and Solar Panel Cleaning ... - EnergyPortal.eu

In a significant advancement in robotics, Google DeepMind has introduced a new AI agent named RoboCat. This agent is designed to learn a variety of tasks across different robotic arms, showcasing the ability to self-generate new training data to improve its techniques, marking a crucial step towards the creation of general-purpose robots.

RoboCat, a Transformer model with a VQ-GAN encoder, was released in June 2023. It is primarily intended for research into learning to accomplish a wide variety of tasks from expert demonstrations or multiple real robot embodiments for manipulation.

The primary intended users are Google DeepMind researchers, and it's not intended for commercial or production use.

RoboCat's standout feature is its learning speed. It can master a new task with as few as 100 demonstrations, leveraging a large and diverse dataset. This capability reduces the need for human-supervised training, potentially accelerating the pace of robotics research.

RoboCat's training involves a comprehensive five-step self-improvement process. It starts with collecting 100-1000 demonstrations of a new task or robot, using a robotic arm controlled by a human. This new task or arm data is used to fine-tune RoboCat, creating a specialized spin-off agent. This agent practices the new task or arm an average of 10,000 times, generating more training data.

The demonstration data and self-generated data are then incorporated into RoboCats existing training dataset, and a new version of RoboCat is trained on the updated dataset.

This process enables RoboCat to learn from a wide range of tasks and diverse training data types. Having been trained on millions of trajectories from both real and simulated robotic arms, RoboCat handles a variety of tasks involving different objects and variations, sourced from Reinforcement Learning (RL), Teleoperation (Teleop), and RoboCat itself.

These tasks include stacking RGB objects, tower and pyramid building with RGB objects, and lifting NIST-i gears, among others. The training involved four different types of robots and many robotic arms to collect vision-based data representing the tasks RoboCat would be trained to perform.

RoboCat demonstrates impressive adaptability by quickly learning to operate different robotic arms. For example, after observing 1000 demonstrations controlled by humans, RoboCat could successfully direct a new arm with a three-fingered gripper and twice as many controllable inputs, achieving an 86% success rate in picking up gears.

Moreover, the more new tasks RoboCat learns, the better it gets at learning additional new tasks. The initial version of RoboCat achieved a 36% success rate on previously unseen tasks after learning from 500 demonstrations per task. However, the latest version, trained on a more diverse set of tasks, more than doubled this success rate on the same tasks.

RoboCat's performance was evaluated through various tasks, such as inserting and removing objects from a bowl and lifting large gears. These evaluations were conducted in both simulated and real-world environments and compared to the performance of human teleoperators.

During the training process, RoboCat uses different observations to understand the robot's position and grip. These observations include joint angles, TCP position, gripper joint angle, and gripper grasp status. The specific observations depend on the robot and objects being used.

In the development of RoboCat, an interesting comparison was made between the VQ-GAN tokenizer and the patch ResNet used in Gato. The patch ResNet tokenizer performed better during training tasks but performed worse on tasks that were not included during training.

It's important to note that RoboCat is currently an early research model and has not been evaluated for deployment and safety outside of research environments. As RoboCat's capabilities expand, potential ethical and safety risks need to be carefully addressed. Therefore, caution should be exercised when considering the use of RoboCat outside of research settings. Nonetheless, the development of RoboCat represents a significant milestone in the field of robotics and AI, bringing us closer to a future where robots are an integral part of our everyday lives.

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RoboCat: Google DeepMind's innovative leap into AI-powered ... - The Jerusalem Post

ChatGPT and Epic Systems

This years buzzword in academic and now business technology is ChatGPT. Epic Systems, Microsoft, and OpenAI (the owners of ChatGPT) have announced the release of the next evolution in artificial intelligence (AI) called GPT-4. This new system integrates AI with electronic health records with the hopes of advancing medical care and associated services.

In-basket messaging is the first section of electronic health records that will be significantly changed. Typically, provider emails, phone calls, and patient messages are loaded in chronological order. With the integration and advancement of AI, in-basket messages are prioritized and distributed to make the most efficient use of provider time.

Presenters at HIMSS 2023 lectured about the potential application of language models like GPT-4 for automating clinical documentation, decision support, and prescribing. This advancement is done by software that has been trained using a language model on a large dataset of health care-related messages and responses. Eventually, it may be possible to develop a system that can generate appropriate responses to different types of in-basket messages automatically.

However, it is important to note that the use of such systems would need to be carefully monitored and controlled to ensure that patient privacy and confidentiality are maintained at all times. Additionally, a health care provider must carefully review any automated response generated by a language model to ensure that it is accurate and appropriate for the specific context.

Mixed reality (medical extended reality)

Medical extended reality (MXR) or the use of virtual, augmented, and mixed reality technologies in health care is a relatively new field that is being explored for its potential to improve patient care and medical training. Exhibits at the conference demonstrated a variety of ways that MXR can be used, such as medical training, patient education, pain management, and patient rehabilitation.

In the realm of medical training, MXR can be used to simulate medical scenarios and procedures for training purposes. Medical students, nurses, and training allied professionals can use virtual and augmented reality to practice surgical procedures, diagnose medical conditions, or learn about human anatomy.

Medical extended reality can also be used to educate patients about their medical conditions and treatment options. For example, virtual reality can be used to show patients what happens during a surgical procedure or how their medications work in their bodies. It is hoped that using this advanced technology can help in some of the most pressing aspects of modern medical care, such as pain management. For instance, it can be used to distract patients from pain and discomfort post-medical procedures, similar to using a mirror box to relieve a patients pain after a limb amputation.

Lastly, MXR has the potential to aid in the rehabilitation of patients. Virtual and augmented reality can be used to simulate real-world scenarios and activities to help patients recover from injuries and improve their motor skills. There are a number of potential ways to improve patient outcomes and enhance medical education and training. However, it is important to note that MXR is still in the early stages of development, and more research is needed to fully understand its potential benefits and limitations.

Robotics (Cobot)

ChristianaCare has integrated cobots, short for collaborative robots; it is a type of robot designed to assist their medical staff. Cobots complete various tasks throughout the hospital, including reducing the need for human workers to move heavy or bulky items. This can help reduce the risk of workplace injuries and improve efficiency. Cobots are also being used at pharmacies to automate tasks such as medication dispensing and inventory management. It is theorized that this type of automation can help reduce errors and improve efficiency. Overall, cobots are not replacements for human workers but rather a tool to augment their capabilities and improve their working conditions.

Fast Healthcare Interoperability Resources (FHIR)

Fast Healthcare Interoperability Resources intend to deliver the exchange of health care information between different EHR systems. This product helps existing EHR software come into compliance with the EHR interoperability requirements created by the 21st Century Cures Act. Unfortunately, there needs to be much improvement for FHIR to be more meaningful.

Another exciting advancement announced at the HIMSS 23 conference was the partnership between Oracle Health and Athena Health to explore the potential use of biometrics (face recognition directory) to verify the identity of providers. This could be used to increase efficiency for prescribing controlled substances. Many of these exciting developments are still in the planning stages and may not come to fruition.

Afua Aningis a physician informaticist.

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Seen at HIMSS: the latest innovations in artificial intelligence, mixed ... - Kevin MD

LAS VEGAS, June 29, 2023 /PRNewswire/ --KEENON Robotics proudly participated in and sponsored The Hospitality Show 2023, showcasing it's innovative hotel robotics technology and solutions. As a leading global robotic service provider, KEENON Robotics delivered an exceptional robot service experience to attendees, highlighting their commitment to advancing the service robot industry.

The Hospitality Show, a premier hospitality industry event in North America, is the brainchild of AHLA (The American Hotel and Lodging Association, the largest hotel association in the U.S.) and Hotel Management Magazine (the premier source of information about the hotel industry for more than 140 years). It is one of the main hospitality industry event in North America, aimed at driving operational efficiency and profitability in hotels.

As an official sponsor, KEENON Robotics showcased seven hotel and restaurant robots, with BUTLERBOT W3, DINERBOT T9 PRO and GUIDERBOT G2 stationed in the exhibition hall to provide services for information consultation, guidance, and distribution of exhibition materials to attendees. Attendees were impressed by the robots' capabilities and their significant contribution to streamlining the exhibition front desk.

KEENON BUTLERBOT W3 delivered a personalized and privacy-focused hotel service with front desk reception and 24-hour room delivery capabilities. These robots autonomously navigated elevators, optimizing workflow and enhancing operational efficiency. They also minimized human errors, provided real-time data analysis, and assisted hotel management in decision-making, resulting in improved effectiveness and profitability. By enhancing service efficiency and reducing operating costs, KEENON BUTLERBOT alleviates the workload on staff, allowing them to focus on delivering exceptional customer experiences.

KEENON Robotics eagerly anticipates collaborating with industry stakeholders to explore the future of the hotel industry and collectively work towards intelligent, efficient, and sustainable hotel services.

About KEENON Robotics:

KEENON Robotics is a global leader in cutting-edge service robots and solutions that transform businesses and enhance customer experiences. Since 2010, KEENON Robotics has been at the forefront of the service robot revolution, leveraging the latest technologies in robotics and cloud computing. Their advanced robots cater to various sectors, including delivery, hospitality, retail, and education. As a trusted partner, KEENON Robotics is dedicated to creating value, driving innovation, and contributing to the growth of the service robot industry.

SOURCE Keenon Robotics Co., Ltd.

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KEENON Robotics Empowers Future of Hotel Experiences as ... - PR Newswire

Here is a brief overview of investing in robotics in 2023 will offer the potential for returns

Investing in robotics can be a promising opportunity for investors looking to tap into the future of technology. The robotics industry is experiencing rapid growth and is poised to revolutionize various sectors, including manufacturing, healthcare, transportation, and more.

The growth of robotics is mainly influenced by automation. As businesses strive for increased efficiency, they turn to robotics to streamline operations and reduce costs. The advantages of investing in robotics are providing exposure to an industry with immense potential, the robotic companies operating in niche markets create opportunities for differentiation, and investing allows diversification within the broader technology sector, reducing risk. This remarks that advancements in the field of robotics have been revolutionalizing the way we live and work. This brief overview of investing in robotics in 2023 highlights key trends, potential investment areas, and considerations for those interested in venturing into the world of robotics.

The increasing adoption of automation across various sectors creates a strong demand for robotics solutions. This demand is expected to fuel significant revenue growth for robotics companies. These companies can capitalize on the expanding market and drive their revenue growth by offering advanced technologies and robotic systems that enhance efficiency, reduce costs, and improve productivity.

The robotics market continues to expand rapidly, driven by increased automation, advancements in artificial intelligence (AI), and the need for enhanced productivity and efficiency across various sectors. In 2023, the market is projected to reach new heights, with a focus on the following trends:

While robotics encompasses a wide range of applications, several key areas stand out as potential investment opportunities:

Investing in robotics, like any other industry, requires careful evaluation and consideration of several factors:

However, its important to consider potential risks. Rapid technological advancements may lead to obsolescence, and competition in the industry is intensifying. Additionally, regulatory challenges and ethical concerns surrounding robotics could impact the industrys growth.

Overall, investing in robotics can be an exciting venture, offering the potential for substantial returns. As with any investment, thorough research, diversification, and a long-term perspective are essential to make informed investment decisions in the rapidly evolving robotics landscape.

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Brief Overview of Investing in Robotics in 2023 - Analytics Insight

Two years after introducing LiBiao robotic parcel sortation technology at its sorting centre in Athens, Hellenic Post (ELTA), the state-owned provider of postal services in Greece, has introduced additional robots, chutes and induction stations at the site.

The investment means throughput capacity at the Athens facility has been significantly increased and allows ELTA to provide next-day delivery services to several additional destinations throughoutGreece.

In all a total of 120 LiBiao autonomous mobile robots (AMR) are now deployed at the sorting centre in Athens. They scan each parcels barcode, weigh the package and, directed by sensors, empty it into the appropriate mail sack sited around the platform on which the robots travel.

Initially introduced as part of ELTAs digital restructuring programme which was established to tackle the growing number of parcels generated by the growth of online shopping, the AMR-based sortation solution has enabled ELTA to improve the efficiency of its workforce by assigning personnel to more productive tasks.

Before the LiBiao sorting system went live, ELTA had undertaken parcel sorting manually which was obviously extremely time consuming and labour intensive. It was also prone to errors which caused parcels to be delayed. Late deliveries were not only frustrating for ELTAs customers and courier partners but also extremely costly for the company.

Since the parcel sorting function has been handed over to the LiBiao robots the process is three times faster, ensuring next-day delivery, while errors have been virtually eliminated.

With the additional robots, ELTA can now handle close to 125,000 parcels weighing up to 10 kg every day and, because each robot only needs to be recharged for five minutes every four hours, on-site power consumption and energy costs are minimised.

Based on the performance of the first phase of the installation ELTA expect this latest investment to pay for itself within two years.

Evi Arguriadou, ELTAs head of sorting operations, comments: Since the introduction of robotic technology our Athens facility has come to be regarded as a centre of excellence within our industry. We regularly host visits from executives from other parcel delivery services companies across Europe who are interested in the technology we have deployed. We are happy and proud to do so.

LiBiao Robotics founder and CEO, Xia Hulling,commented: The initial installation at ELTA and the recent extension highlights perfectly why LiBiao autonomous mobile robot (AMR)-based sortation technology is proving an attractive alternative tothe high CapEx fixed tilt-tray and cross-belt conveyor-based systems that have historically been used within many busy parcel and e-commerce operations.

Xia Hulling continued: With no fixed infrastructure requirements, modular AMR-based systems are scalable and offer complete flexibility with additional robots easily introduced as and when they are needed.

And, I am pleased to say that several of the companies that have visited ELTAs Athens site to see the system in operation for themselves have become LiBiao customers too! she added.

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Greek post office makes further commitment to Robotics parcel ... - Post and Parcel

For people who have suffered neurotrauma such as a stroke, everyday tasks can be extremely challenging because of decreased coordination and strength in one or both upper limbs. These problems have spurred the development of robotic devices to help enhance their abilities. However, the rigid nature of these assistive devices can be problematic, especially for more complex tasks like playing a musical instrument.

A first-of-its-kind robotic glove is lending a "hand" and providing hope to piano players who have suffered a disabling stroke. Developed by researchers from Florida Atlantic University's College of Engineering and Computer Science, the soft robotic hand exoskeleton uses artificial intelligence to improve hand dexterity.

Combining flexible tactile sensors, soft actuators and AI, this robotic glove is the first to "feel" the difference between correct and incorrect versions of the same song and to combine these features into a single hand exoskeleton.

"Playing the piano requires complex and highly skilled movements, and relearning tasks involves the restoration and retraining of specific movements or skills," said Erik Engeberg, Ph.D., senior author, a professor in FAU's Department of Ocean and Mechanical Engineering within the College of Engineering and Computer Science, and a member of the FAU Center for Complex Systems and Brain Sciences and the FAU Stiles-Nicholson Brain Institute. "Our robotic glove is composed of soft, flexible materials and sensors that provide gentle support and assistance to individuals to relearn and regain their motor abilities."

Researchers integrated special sensor arrays into each fingertip of the robotic glove. Unlike prior exoskeletons, this new technology provides precise force and guidance in recovering the fine finger movements required for piano playing. By monitoring and responding to users' movements, the robotic glove offers real-time feedback and adjustments, making it easier for them to grasp the correct movement techniques.

To demonstrate the robotic glove's capabilities, researchers programmed it to feel the difference between correct and incorrect versions of the well-known tune, "Mary Had a Little Lamb," played on the piano. To introduce variations in the performance, they created a pool of 12 different types of errors that could occur at the beginning or end of a note, or due to timing errors that were either premature or delayed, and that persisted for 0.1, 0.2 or 0.3 seconds. Ten different song variations consisted of three groups of three variations each, plus the correct song played with no errors.

To classify the song variations, Random Forest (RF), K-Nearest Neighbor (KNN) and Artificial Neural Network (ANN) algorithms were trained with data from the tactile sensors in the fingertips. Feeling the differences between correct and incorrect versions of the song was done with the robotic glove independently and while worn by a person. The accuracy of these algorithms was compared to classify the correct and incorrect song variations with and without the human subject.

Results of the study, published in the journal Frontiers in Robotics and AI, demonstrated that the ANN algorithm had the highest classification accuracy of 97.13 percent with the human subject and 94.60 percent without the human subject. The algorithm successfully determined the percentage error of a certain song as well as identified key presses that were out of time. These findings highlight the potential of the smart robotic glove to aid individuals who are disabled to relearn dexterous tasks like playing musical instruments.

Researchers designed the robotic glove using 3D printed polyvinyl acid stents and hydrogel casting to integrate five actuators into a single wearable device that conforms to the user's hand. The fabrication process is new, and the form factor could be customized to the unique anatomy of individual patients with the use of 3D scanning technology or CT scans.

"Our design is significantly simpler than most designs as all the actuators and sensors are combined into a single molding process," said Engeberg. "Importantly, although this study's application was for playing a song, the approach could be applied to myriad tasks of daily life and the device could facilitate intricate rehabilitation programs customized for each patient."

Clinicians could use the data to develop personalized action plans to pinpoint patient weaknesses, which may present themselves as sections of the song that are consistently played erroneously and can be used to determine which motor functions require improvement. As patients progress, more challenging songs could be prescribed by the rehabilitation team in a game-like progression to provide a customizable path to improvement.

"The technology developed by professor Engeberg and the research team is truly a gamechanger for individuals with neuromuscular disorders and reduced limb functionality," said Stella Batalama, Ph.D., dean of the FAU College of Engineering and Computer Science. "Although other soft robotic actuators have been used to play the piano; our robotic glove is the only one that has demonstrated the capability to 'feel' the difference between correct and incorrect versions of the same song."

Study co-authors are Maohua Lin, first author and a Ph.D. student; Rudy Paul, a graduate student; and Moaed Abd, Ph.D., a recent graduate; all from the FAU College of Engineering and Computer Science; James Jones, Boise State University; Darryl Dieujuste, a graduate research assistant, FAU College of Engineering and Computer Science; and Harvey Chim, M.D., a professor in the Division of Plastic and Reconstructive Surgery at the University of Florida.

This research was supported by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health (NIH), the National Institute of Aging of the NIH and the National Science Foundation. This research was supported in part by a seed grant from the FAU College of Engineering and Computer Science and the FAU Institute for Sensing and Embedded Network Systems Engineering (I-SENSE).

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Robotic glove that 'feels' lends a 'hand' to relearn playing piano after ... - Science Daily

To students in his University of Toronto lab, Brokoslaw Laschowski is known as the bionic professor a superhuman nickname that speaks to both his fascination with wearable robotics and passion for helping others.

Their work includes bionic prosthetic legs, exoskeletons, AI-powered smart glasses and neural interfaces.

We are trying to help individuals with physical disabilities. Its such a challenging problem, how do you design technology that interface with humans and allows them to synergistically move in a meaningful way?

For Laschowski, who says he has long been fascinated with the concept of cyborgs, computer vision can help seamlessly merge humans with machines.

Humans use their vision for path planning and control, which inspired the use of vision in autonomous cars, he says. I started looking into how we could possibly use vision with walking robots.

For the teams prosthetic leg and exoskeleton, tiny cameras allow the devices to sense their environments in real-time an idea that Laschowski says is unique to his research.

There arent many labs in the world that are using computer vision to improve human-robot walking, he says.

The teams smart glasses interact with both the exoskeleton and bionic prosthetic leg. The system works by combining computer vision and deep-learning AI to recognize the surrounding environment and adapt to obstacles and changes in terrain.

We can accurately and quickly identify features of the environment and relay that information to the bionic legs, he says.

Laschowski says he became passionate about assistive technology while he was pursuing his second masters degree at the University of Waterloo. At the time, he was working with Paralympic athletes from Team Canada on design optimization of wheelchairs using computer simulations.

He completed a PhD in engineering at Waterloo before coming to U of T to do a postdoctoral fellowship in the Temerty Faculty of Medicine.

Laschowskis drive to help others extends well beyond the realm of assistive devices.

Last year, he worked with Michael Brudno, chief data scientist for the University Health Network and a professor of computer science in the Faculty of Arts & Science, to launch a summer research program for students fleeing the Russian invasion and war in Ukraine.

As a Ukrainian-Canadian, Laschowski says the initiative is close to his heart.

We took students out of war zones and gave them a safe learning environment especially last year.

We feel a huge sense of responsibility, Laschowski says. They are under our care. We promised that we would help them while their brothers and fathers are fighting for freedom.

Oleksii Tsepa, a masters student in computer science at U of T, left his home in Kyiv on the first day of the war, with his parents urging him to go aboard. The borders were still open, he recalls. I understood that I wouldnt be able to leave Ukraine later.

He stayed in Cyprus for a couple of months before finding out about the U of T program.

I feel lucky that I qualified and that I worked with Professor Laschowski, Tsepa says. He taught me that I always have to answer myself. I understood that achievements cant be reached without putting in effort.

The effort put in by Laschowski and his team is evident in their potentially game-changing technologies, which are being tested in environments both inside and outside the lab.

I am a huge proponent of getting out of the lab as fast as possible because these devices are going to have the greatest impact in the real world. Laschowski says.

His lab is also developing neural interfaces, which would give humans direct control over the bionic prosthetic leg and exoskeleton. Far into the future, he imagines hell be working on connecting his smart glasses to a brain implant.

We could potentially map images of the walking environment from the glasses directly onto the visual cortex of the brain essentially bypassing the eyes and giving users bionic vision, he says.

If somebody has macular degeneration or some age-related visual impairment, we may be able to use the smart glasses to bypass that and interface directly to the brain.

Laschowski says he believes humans are beginning to go through a technological evolution one that he is helping to make reality.

If we could allow the visually impaired to see and the paralyzed to walk through advances in technology those are some of my career goals.

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'Bionic professor' aims to transform the field of wearable robotics - University of Toronto

The energy sector is constantly evolving, and as the world moves towards cleaner and more sustainable energy sources, the need for efficient and safe maintenance of energy infrastructure becomes increasingly important. One of the most promising solutions to this challenge is the adoption of robotics. The integration of advanced robotics technologies into the maintenance of energy infrastructure offers numerous advantages, including enhanced safety, increased efficiency, and reduced costs.

Safety is a top priority in the energy sector, and the use of robotics can significantly improve the safety of workers involved in the maintenance of energy infrastructure. Many maintenance tasks, such as inspecting pipelines, power lines, and wind turbines, can be hazardous and require workers to operate in dangerous environments. By utilizing robotics, these tasks can be performed remotely, reducing the risk of accidents and injuries. For example, drones equipped with high-resolution cameras and sensors can inspect power lines and pipelines from a safe distance, while robotic crawlers can navigate through confined spaces to perform inspections and repairs.

In addition to improving safety, robotics can also increase the efficiency of energy infrastructure maintenance. Traditional methods of inspection and maintenance can be time-consuming and labor-intensive, often requiring manual processes and the use of heavy equipment. Robotics can automate many of these tasks, allowing for faster and more accurate inspections and repairs. For instance, autonomous underwater vehicles (AUVs) can be used to inspect offshore oil and gas platforms, while robotic arms can perform maintenance tasks on wind turbines, such as cleaning and repairing blades. This increased efficiency can lead to reduced downtime and improved productivity, ultimately resulting in cost savings for energy companies.

The adoption of robotics in energy infrastructure maintenance can also lead to significant cost savings. The use of robotics can reduce the need for manual labor, which can be expensive and difficult to find, especially in remote locations. Additionally, the increased efficiency and reduced downtime associated with robotic maintenance can lead to lower operating costs. Furthermore, the use of robotics can extend the lifespan of energy infrastructure by enabling more frequent and thorough inspections, identifying potential issues before they become critical and costly to repair.

Another advantage of adopting robotics for energy infrastructure maintenance is the ability to collect and analyze large amounts of data. Advanced sensors and cameras on robotic systems can capture high-resolution images and other data during inspections, which can be used to create detailed digital models of the infrastructure. This data can then be analyzed using artificial intelligence and machine learning algorithms to identify patterns and trends, allowing for predictive maintenance and more informed decision-making. This data-driven approach can help energy companies optimize their maintenance strategies, further reducing costs and improving the overall performance of their infrastructure.

In conclusion, the adoption of robotics in the maintenance of energy infrastructure offers numerous advantages, including enhanced safety, increased efficiency, and reduced costs. As the energy sector continues to evolve and the demand for clean and sustainable energy sources grows, the integration of advanced robotics technologies will become increasingly important in ensuring the safe and efficient operation of energy infrastructure. By embracing robotics, energy companies can not only improve the safety and well-being of their workers but also ensure the long-term sustainability and success of their operations.

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