Walking, running, and jumping — a new approach to these surprising challenges for robots
UW ECE Associate Professor Sam Burden is part of a multi-institutional research team that examined why legged locomotion is challenging for robots as compared to humans and other animals. The team published their findings in Science Robotics.
The University of Washington is at the forefront of an international effort to innovate the semiconductor industry while building a skilled U.S.-based workforce to design and manufacture chip technology. UW ECE and Physics Professor Mo Li is leading the UW's contribution to this effort.
UW joins $110M cross-Pacific effort to advance artificial intelligence
The UW joins a landmark $110 million cross-Pacific effort and will partner with Amazon, NVIDIA and the University of Tsukuba, Japan, to advance artificial intelligence.
UW ECE alumnus and Affiliate Professor Jai Jaisimha (Ph.D. ‘96) has co-founded a new nonprofit organization, the Transparency Coalition.ai, which is advocating for transparency and regulation of the data used to train artificial intelligence.
Q&A: How to train AI when you don’t have enough data
Sarah McQuate from UW News recently interviewed UW ECE Professor Jenq-Neng Hwang about his research and how his team trains machine learning algorithms for artificial intelligence using limited data sets.
UW ECE Associate Professor Sam Burden is part of a multi-institutional research team that examined why legged locomotion is challenging for robots as compared to humans and other animals. The team published their findings in Science Robotics.
The University of Washington is at the forefront of an international effort to innovate the semiconductor industry while building a skilled U.S.-based workforce to design and manufacture chip technology. UW ECE and Physics Professor Mo Li is leading the UW's contribution to this effort.
The UW joins a landmark $110 million cross-Pacific effort and will partner with Amazon, NVIDIA and the University of Tsukuba, Japan, to advance artificial intelligence.
UW ECE alumnus and Affiliate Professor Jai Jaisimha (Ph.D. ‘96) has co-founded a new nonprofit organization, the Transparency Coalition.ai, which is advocating for transparency and regulation of the data used to train artificial intelligence.
Sarah McQuate from UW News recently interviewed UW ECE Professor Jenq-Neng Hwang about his research and how his team trains machine learning algorithms for artificial intelligence using limited data sets.
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[post_content] => By Wayne Gillam / UW ECE News
[caption id="attachment_34231" align="alignright" width="575"] UW ECE Associate Professor Sam Burden is part of a multi-institutional research team that examined why walking, running, and jumping are challenging tasks for robots while the same activities appear to be relatively easy for humans and other animals. The team published their findings in a recent issue of the journal Science Robotics. Photo by Nicolas Thomas / Unsplash[/caption]
Over the last few years, millions of people have watched videos of robots walking, running, and jumping with breathtaking power, agility, and speed. However, what many people don’t realize is that these videos are carefully choreographed and take place in tightly controlled environments. In the real world, outside of those controls, legged robots still have a long way to go to match what humans and other animals can do.
It turns out that walking, running, and jumping, or “legged locomotion,” as it’s known in engineering circles, is surprisingly difficult for robots, especially when it comes to achieving dynamic mobility in an uncontrolled environment. Digital, programmable robots have been around for decades now, but compared to animals, their skill at legged locomotion in the real world is barely out of its infancy. That’s not so bad when one considers that animals have had millions of years to evolve and perfect their moves. It even takes a human toddler several years to learn how to walk, run, and jump. So, with those points in mind, perhaps it’s not quite as surprising that it’s taking scientists and engineers a long time to master this difficult skill set on behalf of robots. But why are walking, running, and jumping such challenging tasks for robots, when the same activities seem to be relatively easy for animals?
In a new paper titled, “Why animals can outrun robots,” which was recently published in the journal Science Robotics, a multidisciplinary, multi-institutional research team that included UW ECE Associate Professor Sam Burden examines in depth why this might be.
“If you look at a squirrel, for example, it’s amazing what they can do. And there’s just no comparison at any scale or any kind of modality for legged robots,” Burden said. “The point of this paper is to synthesize across biology and engineering what we know about the components and the whole systems involved and try to answer the question of why animals are so much better at legged locomotion than robots.”
[caption id="attachment_34233" align="alignright" width="350"] UW ECE Associate Professor Sam Burden[/caption]
Burden’s collaborators included Max Donelan, a professor at Simon Fraser University in biomedical physiology and kinesiology; Kaushik Jayaram, an assistant professor in the Paul M. Rady Department of Mechanical Engineering at the University of Colorado Boulder; Simon Sponberg, the Dunn Family Associate Professor of Physics and Biological Sciences at the Georgia Institute of Technology; and Tom Libby, who was a Washington Research Foundation Fellow in Neuroengineering at UW ECE from 2017 to 2019 and is now a senior research engineer at SRI International.
Each researcher in the group explored one of the five engineering subsystems that make up robotic legged locomotion. Together, they dug deep into the scientific literature, investigating and analyzing why animals outperform robots at walking, running, and jumping, and they quantified the differences they found. Before this research, many scientists and engineers believed the main reason animals had a significant advantage over robots was that biological components were superior to engineered parts. But what the team discovered because of their extensive review, was that the opposite was true, and that the whole was far greater than the sum of its parts.
“The way things turned out is that, with only minor exceptions, the engineering subsystems outperform the biological equivalents — and sometimes radically outperform them,” Libby said in a recent press release from Simon Fraser University. “But also, what’s very, very clear is that, if you compare animals to robots at the whole system level, in terms of movement, animals are amazing. And robots have yet to catch up.”
Based on these findings and their intensive examination of engineering subsystems, the team identified in their paper fundamental obstacles that roboticists must overcome to bring robot legged locomotion up to par with humans and other animals. The team also highlighted promising research directions that hold transformative potential to help legged robots achieve animal-level performance.
Engineering subsystems, overcoming obstacles, and promising research directions
The team’s paper was comprehensive in its review of the scientific literature available on this topic. Their research began in 2013 and lasted over a decade, as group members worked on investigation and analysis of legged locomotion in between their other responsibilities.
“In the paper, we divide legged locomotion into five engineering subsystems and cover them all in depth,” Burden said. “Normally, analyzing any single one of these subsystems for either an animal or a robot could be an entire review paper by itself. It’s an ambitious and broad project.”
The five engineering subsystems the team explored were the power system used to store and deliver energy, the frame that provides support and leverage, actuators to modulate mechanical energy, sensors to perceive self and environment, and the control system, which transmits and transforms sensor and actuator signals. For each subsystem, the team compared, contrasted, and quantified differences between legged robots and animals. Burden said that the group wrote this paper primarily for roboticists but that they also wanted their findings to be accessible to biologists to encourage collaboration when tackling the tough problem of improving robotic legged locomotion.
“This paper is rigorously researched, and basically, we’re saying that if you want high performance and want to approach the capabilities of animals, what we need in robotics is an integrative approach. It is not the quality of robotic components that explains this wide performance gap, but rather, how they are put together into a unified whole.” — UW ECE Associate Professor Sam Burden
To that end, the team identified four fundamental obstacles they believe must be overcome to successfully integrate engineered components into more effective robotic systems. Those obstacles are a lack of quantitative metrics for evaluating the many dimensions of legged locomotion; the tradeoffs that arise when subsystems combine and the performance of one component potentially constrains the performance of another; the phenomenon of emergence, where the behavior of the whole system is different from, and irreducible to, the behavior of its component parts; and the very Harry Potter-sounding curse of dimensionality, which means that there is a mind-boggling array of possible component configurations roboticists can choose from when designing legged robots and very little guidance as to which will be the most effective.
To not leave scientists and engineers without paths to solutions, the researchers also identified several promising research directions. Those include systematic comparative studies of multiple animal species, which could reveal generalizable principles that could be applied to robotics; distributing energy, sensing, actuation, and control throughout robot frames, as animals do, which may enhance robustness and advance autonomy; bridging the “sim-to-real” gap with better computational models of robot interactions with the environment; continuing advances in materials used to build robotics, and systematically exploring tradeoffs with respect to multiple performance metrics at both component and system levels.
Overall, the research team emphasized that although further improvements to robotic components are beneficial, the greatest opportunity to improve the performance of legged robots is to make better use of existing parts, much like biological systems do. They advocated in the paper for a more integrated approach to engineering legged robots, taking cues and guidance from biology along the way.
Downstream impacts, ethical considerations, and looking ahead
[caption id="attachment_34245" align="alignright" width="350"] Burden and his colleagues are optimistic that over the long term, when it comes to developing robots that can walk, run, and jump as well as or better than humans and other animals, the benefits will far outweigh the risks. Photo courtesy of the Animal Inspired Movement and Robotics Lab / University of Colorado Boulder[/caption]
By developing a better understanding of the principles involved in legged locomotion for both animals and robots, Burden and his colleagues have moved the field of robotics closer toward a longstanding goal for engineers — creating robots that can walk, run, and jump as well as (and perhaps even better than) humans and other animals. There are many reasons why this is an important, worthy goal. Legged robots with robust agility could perform many useful, and even life-saving, tasks in environments that are hazardous for humans, such as cleaning up after natural and nuclear disasters, disarming bombs, or helping astronauts explore outer space. Principles learned from this robotic development could also be applied to advanced, bio-inspired devices, such as smart prosthetic limbs and exoskeletons. And the potential everyday applications are endless, including developing legged robots to clean the house, do yard work, and even care for the elderly. The automation of various tasks by legged robots across a vast range of industries also promises to substantially enrich the world economy.
But, of course, every powerful technology can be a double-edged sword, and there are some downsides to consider. Robotic automation could enrich the economy, but that will be at the cost of job loss for at least some humans. This could happen in large numbers and at such a rapid pace, it would be hard for society to adjust. The possible weaponization of legged robots also is a serious concern, and some manufacturers are calling on the robotics community and government leaders to take steps to ensure this doesn’t happen. Recently, some thought leaders have suggested that the fear of job loss from robotics is overblown; however, whether or not they are right still remains to be seen. In the meantime, roboticists, industry leaders, and government representatives are exploring different avenues for addressing these sorts of concerns, and that work is ongoing.
Burden and his colleagues are optimistic that over the long term, when it comes to developing robots that can walk, run, and jump as well as or better than humans and other animals, the benefits will far outweigh the risks.
“These are machines that could have a really big, positive impact on people’s lives, but they’re just not capable yet,” Burden said. “This paper is rigorously researched, and basically, we’re saying that if you want high performance and want to approach the capabilities of animals, what we need in robotics is an integrative approach. It is not the quality of robotic components that explains this wide performance gap, but rather, how they are put together into a unified whole.”
Learn more about this research by reading “Why animals can outrun robots” in Science Robotics. More information about UW ECE Associate Professor Sam Burden is available on his bio page.
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[post_content] => By Wayne Gillam | UW ECE News
[caption id="attachment_34126" align="alignright" width="575"] UW ECE alumnus and Affiliate Professor Jai Jaisimha (Ph.D. ‘96) has co-founded a new nonprofit organization, the Transparency Coalition.ai, which is advocating for transparency and regulation of the data used to train artificial intelligence. / Photo by Igor Omilaev, courtesy of the Transparency Coalition.ai[/caption]
Artificial intelligence holds great promise as well as possible peril for society. This rapidly evolving technology stands to accelerate advances in science, engineering, and healthcare as well as improve efficiency and productivity in a vast range of industries. But AI also has serious downsides, which include the potential to spread misinformation and disinformation online, exacerbate algorithmic biases, compromise individual privacy, and even obliterate copyright protections for intellectual property.
It is the peril of AI that drew the attention of UW ECE alumnus and Affiliate Professor Jai Jaisimha (Ph.D. ‘96), who has worked as a technology entrepreneur for decades and has held leadership positions in major tech companies that leverage AI, such as Amazon and Microsoft. Now, along with his co-founder Rob Eleveld, Jaisimha has created a new nonprofit organization, the Transparency Coalition.ai, which seeks to address these concerns by advocating for greater transparency and regulation of the data used to train and inform AI and generative AI models, such as ChatGPT.
“Rob and I were concerned about the rollout of generative AI and how it was going. We were already seeing evidence of societal harm. And we knew that we had the expertise needed to help address some of these issues,” Jaisimha said. “Because of my work in computer vision and imaging when I was at the UW, I spent years studying and understanding pattern recognition, how it worked, and the mathematics behind it. I built early versions of these AI models that are similar to the ones that are out there now.”
[caption id="attachment_34130" align="alignleft" width="250"] UW ECE alumnus and Affiliate Professor Jai Jaisimha[/caption]
The roots of Jaisimha’s knowledge about AI models and the data used to train them goes back to his time as a doctoral student working with his adviser, UW ECE Professor Emeritus Eve Riskin, who is now the dean of undergraduate education in the electrical and computer engineering department at the Stevens Institute of Technology. With oversight by Riskin, Jaisimha applied statistical pattern recognition techniques to better understand datasets and how to use them to make online browsing a more interactive and personalized experience. During this time, he also had an internship at a startup that did research for government agencies, which taught him the importance of data curation as well as algorithmic model construction, testing and validation.
These experiences as a student carried over into his professional life, which has been defined by his entrepreneurial ventures and corporate leadership.
“When you’re building a company, it’s not just about making a cool demo,” Jaisimha said. “It’s about making sure you have the entire pipeline of AI model building in place: data collection, data cleansing, being rigorous about validating and testing your results, and automating performance monitoring. That way, you end up building a robust system. Those are all things I learned at UW ECE.”
The Transparency Coalition.ai
According to Jaisimha, there is a large amount of research available about ethical and responsible AI development, and many companies have even formed entire departments focused on the ethical implementation of AI in their products. However, profit incentives have interfered with these good intentions. Teams focused on ethical AI in companies are often shrunk or even shut down. And thoughtful research in this area is too often ignored by industry leaders in favor of getting products to market faster and increasing profits.
Jaisimha and his colleagues at the Transparency Coalition.ai believe that the government has an important role to play in regulating AI and providing needed oversight in a highly competitive marketplace. They have chosen to focus their efforts on advocating for greater transparency in AI training data, which Jaisimha believes is key to promoting more ethical and responsible AI development.
Jaisimha said that focusing on AI training data is important because today’s generative AI models are ingesting large amounts of uncurated data. This includes copyrighted material and content behind paywalls, in social media and on personal websites, and even illicit and illegal content, such as child pornography. This indiscriminate ingestion of large amounts of uncurated data makes generative AI systems prone to frequent and well-documented “hallucinations,” where the system provides warped images or wrong and misleading answers when prompted.
"Because I’m an affiliate professor in UW ECE, I’ve been able to tap into the wider UW ecosystem, whether it’s the RAISE group, or computer science and engineering, or linguistics, or law. There’s a lot of good thinking happening across the university, and I’m looking for ways to bring it forward to legislators and to the public." — UW ECE alumnus and Affiliate Professor Jai Jaisimha
In contrast, a generative AI model with a transparent, curated dataset is less prone to hallucinations, greatly reduces the risk for societal harm, and is customized for solving specific problems. In many cases, the curation of training data also optimizes the AI model to accomplish tasks more efficiently. Because of these facts, Jaisimha believes that transparent, regulated, and curated AI training data will not only be good for society, in the long-term, it will be good for business too.
“If you want to solve real-world problems, you have to embrace the idea of either taking these big, generative AI models and refining them for a specific application or building the model in a way that acknowledges that need for customization from the beginning,” Jaisimha said. “We know it’s possible to implement some degree of constraint on AI training data. And I believe the result will be a thriving ecosystem of companies building technologies that will be more practical, useful, and focused on solving real-world problems.”
The Transparency Coalition.ai has set its sights on state-level advocacy, and it is reaching out to legislators in Washington and California. According to Jaisimha, state governments can often move to implement policy more rapidly than the federal government. Washington and California are also headquarters for a high number of leading technology companies working with artificial intelligence, which widens the impact of policies and legislation enacted in these states nationally and internationally.
Since its founding in October 2023, the Transparency Coalition.ai has already scored a significant victory. A bill establishing a new AI Task Force for the state of Washington was signed into law by Governor Jay Inslee last month. Among its other mandates, the Task Force will be considering appropriate regulation for AI training data, which is something the Transparency Coalition.ai advocated for among legislators involved in establishing the group.
At the UW, Jaisimha is collaborating with Professor Chirag Shah in the UW Information School, who runs the Responsibility in AI Systems and Experiences, or RAISE, team at the University. RAISE conducts high-quality research on ethical and responsible AI development, and Jaisimha is connecting the organization with Washington state legislators through the Transparency Coalition.ai to help better inform AI policy and regulation.
UW connections
Jaisimha became a UW ECE affiliate professor in September 2023, and going forward, he plans to retain and continue to grow his connections at the UW. In addition to being affiliated with RAISE and advising student teams in the Department’s Engineering Innovation and Entrepreneurship capstone program, known as ENGINE, he is involved in CoMotion at the UW. There, he is a mentor for students and faculty and is actively involved in the CoMotion Innovation Gap Fund, which helps to move UW inventions and innovations into commercial investment and development. Jaisimha also has several family connections to the University. His wife received her master’s degree in business administration from the Foster School of Business, and their eldest son will be graduating this year from UW ECE with a bachelor’s degree. Their youngest son is a sophomore studying informatics at the UW iSchool.
“We say in our family that we ‘bleed purple.’ The four of us are deeply connected to the UW, and I have a strong sense of needing to pay it forward,” Jaisimha said. “I see both my affiliate work at UW ECE and my mentorship work at CoMotion as a form of giving back. The Transparency Coalition.ai is also a form of giving back to the community.”
Jaisimha encourages students pursuing careers in AI development to not worry too much about whether what they are studying now will remain relevant in this fast-changing world. Instead, he notes there is a specific way of breaking down problems that engineering students learn, which is a useful skill to apply in many situations. He also recommends that students interested in AI explore edge technology, such as TinyML, which brings machine learning networks into resource-constrained devices. And he suggests that students consider taking statistics classes, which can help an ECE graduate stand out in fields related to AI and machine learning.
In regard to his work with the Transparency Coalition.ai, Jaisimha and his co-founder are continuing their outreach to state legislators and seeking donor support for their efforts. He encourages everyone who can to get involved and contact their state legislators to let them know about the need for AI transparency and oversight. To this end, the Transparency Coalition.ai recently installed a bill tracker on their website, which helps make it easy for people to see what bills related to AI are active in their state. Jaisimha also plans to continue to bring pertinent information about AI development to government officials going forward.
“Because I’m an affiliate professor in UW ECE, I’ve been able to tap into the wider UW ecosystem, whether it’s the RAISE group, or computer science and engineering, or linguistics, or law. There’s a lot of good thinking happening across the university, and I’m looking for ways to bring it forward to legislators and to the public,” Jaisimha said. “I’ve never stopped educating myself. Now that I’m back at the UW, I’m continuing my education and benefiting from being at one of the greatest institutions in the world.”
For more information about UW ECE Affiliate Professor Jai Jaisimha and his advocacy work, visit the Transparency Coalition.ai website.
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[post_content] => [caption id="attachment_34048" align="alignright" width="523"] UW ECE Assistant Professor Jungwon Choi's research focuses on designing power circuits that can receive electrical currents at high frequencies from a charging source and transfer the energy to the battery. Shown above, Choi with UW ECE graduate student Manas Palmal.[/caption]
Adapted from an article by Brooke Fisher, Photos by Dennis Wise | UW College of Engineering
Imagine rolling into a parking spot and your electric vehicle (EV) automatically begins to charge, quickly and without cables, thanks to a compact charging station on the ground. UW ECE Assistant Professor Jungwon Choi can do more than envision it — she’s developing the technology.
“Charging time is a barrier for people buying EVs,” Choi says. “I’m interested in how we can make more efficient power circuits to charge the battery in electric vehicles.”
To enhance EV charging, Choi is involved in research on many levels. In addition to advancing the design of spiral coils for high-frequency wireless charging — in which power is transmitted electromagnetically between coils located in a vehicle and charging station — her primary research focuses on designing power circuits that can receive electrical currents at high frequencies from a charging source and transfer the energy to the battery.
[caption id="attachment_34073" align="alignleft" width="418"] UW ECE graduate student Ghovindo Surya turns the knob on an oscilloscope to test the electrical currents received by the power circuit.[/caption]
“We want to have high efficiency,” Choi explains. “When we have 100% power at input and the battery receives only 80% power, then it’s lost as heat. It’s harmful for the system and energy is lost.”
A unique feature of power converters that Choi’s team is working to advance is the two-way flow of energy, which would enable EV batteries to store energy that could be utilized as backup power.
“In an emergency situation, or in case of a blackout, we could draw power from a vehicle into a house,” Choi says.
Learn more about how UW engineering research is driven to advance vehicle electrification on the UW College of Engineering website.
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UW ECE Associate Professor Sam Burden is part of a multi-institutional research team that examined why legged locomotion is challenging for robots as compared to humans and other animals. The team published their findings in Science Robotics.
The University of Washington is at the forefront of an international effort to innovate the semiconductor industry while building a skilled U.S.-based workforce to design and manufacture chip technology. UW ECE and Physics Professor Mo Li is leading the UW's contribution to this effort.
The UW joins a landmark $110 million cross-Pacific effort and will partner with Amazon, NVIDIA and the University of Tsukuba, Japan, to advance artificial intelligence.
UW ECE alumnus and Affiliate Professor Jai Jaisimha (Ph.D. ‘96) has co-founded a new nonprofit organization, the Transparency Coalition.ai, which is advocating for transparency and regulation of the data used to train artificial intelligence.
Sarah McQuate from UW News recently interviewed UW ECE Professor Jenq-Neng Hwang about his research and how his team trains machine learning algorithms for artificial intelligence using limited data sets.
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[post_content] => By Wayne Gillam / UW ECE News
[caption id="attachment_34231" align="alignright" width="575"] UW ECE Associate Professor Sam Burden is part of a multi-institutional research team that examined why walking, running, and jumping are challenging tasks for robots while the same activities appear to be relatively easy for humans and other animals. The team published their findings in a recent issue of the journal Science Robotics. Photo by Nicolas Thomas / Unsplash[/caption]
Over the last few years, millions of people have watched videos of robots walking, running, and jumping with breathtaking power, agility, and speed. However, what many people don’t realize is that these videos are carefully choreographed and take place in tightly controlled environments. In the real world, outside of those controls, legged robots still have a long way to go to match what humans and other animals can do.
It turns out that walking, running, and jumping, or “legged locomotion,” as it’s known in engineering circles, is surprisingly difficult for robots, especially when it comes to achieving dynamic mobility in an uncontrolled environment. Digital, programmable robots have been around for decades now, but compared to animals, their skill at legged locomotion in the real world is barely out of its infancy. That’s not so bad when one considers that animals have had millions of years to evolve and perfect their moves. It even takes a human toddler several years to learn how to walk, run, and jump. So, with those points in mind, perhaps it’s not quite as surprising that it’s taking scientists and engineers a long time to master this difficult skill set on behalf of robots. But why are walking, running, and jumping such challenging tasks for robots, when the same activities seem to be relatively easy for animals?
In a new paper titled, “Why animals can outrun robots,” which was recently published in the journal Science Robotics, a multidisciplinary, multi-institutional research team that included UW ECE Associate Professor Sam Burden examines in depth why this might be.
“If you look at a squirrel, for example, it’s amazing what they can do. And there’s just no comparison at any scale or any kind of modality for legged robots,” Burden said. “The point of this paper is to synthesize across biology and engineering what we know about the components and the whole systems involved and try to answer the question of why animals are so much better at legged locomotion than robots.”
[caption id="attachment_34233" align="alignright" width="350"] UW ECE Associate Professor Sam Burden[/caption]
Burden’s collaborators included Max Donelan, a professor at Simon Fraser University in biomedical physiology and kinesiology; Kaushik Jayaram, an assistant professor in the Paul M. Rady Department of Mechanical Engineering at the University of Colorado Boulder; Simon Sponberg, the Dunn Family Associate Professor of Physics and Biological Sciences at the Georgia Institute of Technology; and Tom Libby, who was a Washington Research Foundation Fellow in Neuroengineering at UW ECE from 2017 to 2019 and is now a senior research engineer at SRI International.
Each researcher in the group explored one of the five engineering subsystems that make up robotic legged locomotion. Together, they dug deep into the scientific literature, investigating and analyzing why animals outperform robots at walking, running, and jumping, and they quantified the differences they found. Before this research, many scientists and engineers believed the main reason animals had a significant advantage over robots was that biological components were superior to engineered parts. But what the team discovered because of their extensive review, was that the opposite was true, and that the whole was far greater than the sum of its parts.
“The way things turned out is that, with only minor exceptions, the engineering subsystems outperform the biological equivalents — and sometimes radically outperform them,” Libby said in a recent press release from Simon Fraser University. “But also, what’s very, very clear is that, if you compare animals to robots at the whole system level, in terms of movement, animals are amazing. And robots have yet to catch up.”
Based on these findings and their intensive examination of engineering subsystems, the team identified in their paper fundamental obstacles that roboticists must overcome to bring robot legged locomotion up to par with humans and other animals. The team also highlighted promising research directions that hold transformative potential to help legged robots achieve animal-level performance.
Engineering subsystems, overcoming obstacles, and promising research directions
The team’s paper was comprehensive in its review of the scientific literature available on this topic. Their research began in 2013 and lasted over a decade, as group members worked on investigation and analysis of legged locomotion in between their other responsibilities.
“In the paper, we divide legged locomotion into five engineering subsystems and cover them all in depth,” Burden said. “Normally, analyzing any single one of these subsystems for either an animal or a robot could be an entire review paper by itself. It’s an ambitious and broad project.”
The five engineering subsystems the team explored were the power system used to store and deliver energy, the frame that provides support and leverage, actuators to modulate mechanical energy, sensors to perceive self and environment, and the control system, which transmits and transforms sensor and actuator signals. For each subsystem, the team compared, contrasted, and quantified differences between legged robots and animals. Burden said that the group wrote this paper primarily for roboticists but that they also wanted their findings to be accessible to biologists to encourage collaboration when tackling the tough problem of improving robotic legged locomotion.
“This paper is rigorously researched, and basically, we’re saying that if you want high performance and want to approach the capabilities of animals, what we need in robotics is an integrative approach. It is not the quality of robotic components that explains this wide performance gap, but rather, how they are put together into a unified whole.” — UW ECE Associate Professor Sam Burden
To that end, the team identified four fundamental obstacles they believe must be overcome to successfully integrate engineered components into more effective robotic systems. Those obstacles are a lack of quantitative metrics for evaluating the many dimensions of legged locomotion; the tradeoffs that arise when subsystems combine and the performance of one component potentially constrains the performance of another; the phenomenon of emergence, where the behavior of the whole system is different from, and irreducible to, the behavior of its component parts; and the very Harry Potter-sounding curse of dimensionality, which means that there is a mind-boggling array of possible component configurations roboticists can choose from when designing legged robots and very little guidance as to which will be the most effective.
To not leave scientists and engineers without paths to solutions, the researchers also identified several promising research directions. Those include systematic comparative studies of multiple animal species, which could reveal generalizable principles that could be applied to robotics; distributing energy, sensing, actuation, and control throughout robot frames, as animals do, which may enhance robustness and advance autonomy; bridging the “sim-to-real” gap with better computational models of robot interactions with the environment; continuing advances in materials used to build robotics, and systematically exploring tradeoffs with respect to multiple performance metrics at both component and system levels.
Overall, the research team emphasized that although further improvements to robotic components are beneficial, the greatest opportunity to improve the performance of legged robots is to make better use of existing parts, much like biological systems do. They advocated in the paper for a more integrated approach to engineering legged robots, taking cues and guidance from biology along the way.
Downstream impacts, ethical considerations, and looking ahead
[caption id="attachment_34245" align="alignright" width="350"] Burden and his colleagues are optimistic that over the long term, when it comes to developing robots that can walk, run, and jump as well as or better than humans and other animals, the benefits will far outweigh the risks. Photo courtesy of the Animal Inspired Movement and Robotics Lab / University of Colorado Boulder[/caption]
By developing a better understanding of the principles involved in legged locomotion for both animals and robots, Burden and his colleagues have moved the field of robotics closer toward a longstanding goal for engineers — creating robots that can walk, run, and jump as well as (and perhaps even better than) humans and other animals. There are many reasons why this is an important, worthy goal. Legged robots with robust agility could perform many useful, and even life-saving, tasks in environments that are hazardous for humans, such as cleaning up after natural and nuclear disasters, disarming bombs, or helping astronauts explore outer space. Principles learned from this robotic development could also be applied to advanced, bio-inspired devices, such as smart prosthetic limbs and exoskeletons. And the potential everyday applications are endless, including developing legged robots to clean the house, do yard work, and even care for the elderly. The automation of various tasks by legged robots across a vast range of industries also promises to substantially enrich the world economy.
But, of course, every powerful technology can be a double-edged sword, and there are some downsides to consider. Robotic automation could enrich the economy, but that will be at the cost of job loss for at least some humans. This could happen in large numbers and at such a rapid pace, it would be hard for society to adjust. The possible weaponization of legged robots also is a serious concern, and some manufacturers are calling on the robotics community and government leaders to take steps to ensure this doesn’t happen. Recently, some thought leaders have suggested that the fear of job loss from robotics is overblown; however, whether or not they are right still remains to be seen. In the meantime, roboticists, industry leaders, and government representatives are exploring different avenues for addressing these sorts of concerns, and that work is ongoing.
Burden and his colleagues are optimistic that over the long term, when it comes to developing robots that can walk, run, and jump as well as or better than humans and other animals, the benefits will far outweigh the risks.
“These are machines that could have a really big, positive impact on people’s lives, but they’re just not capable yet,” Burden said. “This paper is rigorously researched, and basically, we’re saying that if you want high performance and want to approach the capabilities of animals, what we need in robotics is an integrative approach. It is not the quality of robotic components that explains this wide performance gap, but rather, how they are put together into a unified whole.”
Learn more about this research by reading “Why animals can outrun robots” in Science Robotics. More information about UW ECE Associate Professor Sam Burden is available on his bio page.
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[post_title] => UW joins $110M cross-Pacific effort to advance artificial intelligence
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[post_content] => By Wayne Gillam | UW ECE News
[caption id="attachment_34126" align="alignright" width="575"] UW ECE alumnus and Affiliate Professor Jai Jaisimha (Ph.D. ‘96) has co-founded a new nonprofit organization, the Transparency Coalition.ai, which is advocating for transparency and regulation of the data used to train artificial intelligence. / Photo by Igor Omilaev, courtesy of the Transparency Coalition.ai[/caption]
Artificial intelligence holds great promise as well as possible peril for society. This rapidly evolving technology stands to accelerate advances in science, engineering, and healthcare as well as improve efficiency and productivity in a vast range of industries. But AI also has serious downsides, which include the potential to spread misinformation and disinformation online, exacerbate algorithmic biases, compromise individual privacy, and even obliterate copyright protections for intellectual property.
It is the peril of AI that drew the attention of UW ECE alumnus and Affiliate Professor Jai Jaisimha (Ph.D. ‘96), who has worked as a technology entrepreneur for decades and has held leadership positions in major tech companies that leverage AI, such as Amazon and Microsoft. Now, along with his co-founder Rob Eleveld, Jaisimha has created a new nonprofit organization, the Transparency Coalition.ai, which seeks to address these concerns by advocating for greater transparency and regulation of the data used to train and inform AI and generative AI models, such as ChatGPT.
“Rob and I were concerned about the rollout of generative AI and how it was going. We were already seeing evidence of societal harm. And we knew that we had the expertise needed to help address some of these issues,” Jaisimha said. “Because of my work in computer vision and imaging when I was at the UW, I spent years studying and understanding pattern recognition, how it worked, and the mathematics behind it. I built early versions of these AI models that are similar to the ones that are out there now.”
[caption id="attachment_34130" align="alignleft" width="250"] UW ECE alumnus and Affiliate Professor Jai Jaisimha[/caption]
The roots of Jaisimha’s knowledge about AI models and the data used to train them goes back to his time as a doctoral student working with his adviser, UW ECE Professor Emeritus Eve Riskin, who is now the dean of undergraduate education in the electrical and computer engineering department at the Stevens Institute of Technology. With oversight by Riskin, Jaisimha applied statistical pattern recognition techniques to better understand datasets and how to use them to make online browsing a more interactive and personalized experience. During this time, he also had an internship at a startup that did research for government agencies, which taught him the importance of data curation as well as algorithmic model construction, testing and validation.
These experiences as a student carried over into his professional life, which has been defined by his entrepreneurial ventures and corporate leadership.
“When you’re building a company, it’s not just about making a cool demo,” Jaisimha said. “It’s about making sure you have the entire pipeline of AI model building in place: data collection, data cleansing, being rigorous about validating and testing your results, and automating performance monitoring. That way, you end up building a robust system. Those are all things I learned at UW ECE.”
The Transparency Coalition.ai
According to Jaisimha, there is a large amount of research available about ethical and responsible AI development, and many companies have even formed entire departments focused on the ethical implementation of AI in their products. However, profit incentives have interfered with these good intentions. Teams focused on ethical AI in companies are often shrunk or even shut down. And thoughtful research in this area is too often ignored by industry leaders in favor of getting products to market faster and increasing profits.
Jaisimha and his colleagues at the Transparency Coalition.ai believe that the government has an important role to play in regulating AI and providing needed oversight in a highly competitive marketplace. They have chosen to focus their efforts on advocating for greater transparency in AI training data, which Jaisimha believes is key to promoting more ethical and responsible AI development.
Jaisimha said that focusing on AI training data is important because today’s generative AI models are ingesting large amounts of uncurated data. This includes copyrighted material and content behind paywalls, in social media and on personal websites, and even illicit and illegal content, such as child pornography. This indiscriminate ingestion of large amounts of uncurated data makes generative AI systems prone to frequent and well-documented “hallucinations,” where the system provides warped images or wrong and misleading answers when prompted.
"Because I’m an affiliate professor in UW ECE, I’ve been able to tap into the wider UW ecosystem, whether it’s the RAISE group, or computer science and engineering, or linguistics, or law. There’s a lot of good thinking happening across the university, and I’m looking for ways to bring it forward to legislators and to the public." — UW ECE alumnus and Affiliate Professor Jai Jaisimha
In contrast, a generative AI model with a transparent, curated dataset is less prone to hallucinations, greatly reduces the risk for societal harm, and is customized for solving specific problems. In many cases, the curation of training data also optimizes the AI model to accomplish tasks more efficiently. Because of these facts, Jaisimha believes that transparent, regulated, and curated AI training data will not only be good for society, in the long-term, it will be good for business too.
“If you want to solve real-world problems, you have to embrace the idea of either taking these big, generative AI models and refining them for a specific application or building the model in a way that acknowledges that need for customization from the beginning,” Jaisimha said. “We know it’s possible to implement some degree of constraint on AI training data. And I believe the result will be a thriving ecosystem of companies building technologies that will be more practical, useful, and focused on solving real-world problems.”
The Transparency Coalition.ai has set its sights on state-level advocacy, and it is reaching out to legislators in Washington and California. According to Jaisimha, state governments can often move to implement policy more rapidly than the federal government. Washington and California are also headquarters for a high number of leading technology companies working with artificial intelligence, which widens the impact of policies and legislation enacted in these states nationally and internationally.
Since its founding in October 2023, the Transparency Coalition.ai has already scored a significant victory. A bill establishing a new AI Task Force for the state of Washington was signed into law by Governor Jay Inslee last month. Among its other mandates, the Task Force will be considering appropriate regulation for AI training data, which is something the Transparency Coalition.ai advocated for among legislators involved in establishing the group.
At the UW, Jaisimha is collaborating with Professor Chirag Shah in the UW Information School, who runs the Responsibility in AI Systems and Experiences, or RAISE, team at the University. RAISE conducts high-quality research on ethical and responsible AI development, and Jaisimha is connecting the organization with Washington state legislators through the Transparency Coalition.ai to help better inform AI policy and regulation.
UW connections
Jaisimha became a UW ECE affiliate professor in September 2023, and going forward, he plans to retain and continue to grow his connections at the UW. In addition to being affiliated with RAISE and advising student teams in the Department’s Engineering Innovation and Entrepreneurship capstone program, known as ENGINE, he is involved in CoMotion at the UW. There, he is a mentor for students and faculty and is actively involved in the CoMotion Innovation Gap Fund, which helps to move UW inventions and innovations into commercial investment and development. Jaisimha also has several family connections to the University. His wife received her master’s degree in business administration from the Foster School of Business, and their eldest son will be graduating this year from UW ECE with a bachelor’s degree. Their youngest son is a sophomore studying informatics at the UW iSchool.
“We say in our family that we ‘bleed purple.’ The four of us are deeply connected to the UW, and I have a strong sense of needing to pay it forward,” Jaisimha said. “I see both my affiliate work at UW ECE and my mentorship work at CoMotion as a form of giving back. The Transparency Coalition.ai is also a form of giving back to the community.”
Jaisimha encourages students pursuing careers in AI development to not worry too much about whether what they are studying now will remain relevant in this fast-changing world. Instead, he notes there is a specific way of breaking down problems that engineering students learn, which is a useful skill to apply in many situations. He also recommends that students interested in AI explore edge technology, such as TinyML, which brings machine learning networks into resource-constrained devices. And he suggests that students consider taking statistics classes, which can help an ECE graduate stand out in fields related to AI and machine learning.
In regard to his work with the Transparency Coalition.ai, Jaisimha and his co-founder are continuing their outreach to state legislators and seeking donor support for their efforts. He encourages everyone who can to get involved and contact their state legislators to let them know about the need for AI transparency and oversight. To this end, the Transparency Coalition.ai recently installed a bill tracker on their website, which helps make it easy for people to see what bills related to AI are active in their state. Jaisimha also plans to continue to bring pertinent information about AI development to government officials going forward.
“Because I’m an affiliate professor in UW ECE, I’ve been able to tap into the wider UW ecosystem, whether it’s the RAISE group, or computer science and engineering, or linguistics, or law. There’s a lot of good thinking happening across the university, and I’m looking for ways to bring it forward to legislators and to the public,” Jaisimha said. “I’ve never stopped educating myself. Now that I’m back at the UW, I’m continuing my education and benefiting from being at one of the greatest institutions in the world.”
For more information about UW ECE Affiliate Professor Jai Jaisimha and his advocacy work, visit the Transparency Coalition.ai website.
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[post_content] => [caption id="attachment_34048" align="alignright" width="523"] UW ECE Assistant Professor Jungwon Choi's research focuses on designing power circuits that can receive electrical currents at high frequencies from a charging source and transfer the energy to the battery. Shown above, Choi with UW ECE graduate student Manas Palmal.[/caption]
Adapted from an article by Brooke Fisher, Photos by Dennis Wise | UW College of Engineering
Imagine rolling into a parking spot and your electric vehicle (EV) automatically begins to charge, quickly and without cables, thanks to a compact charging station on the ground. UW ECE Assistant Professor Jungwon Choi can do more than envision it — she’s developing the technology.
“Charging time is a barrier for people buying EVs,” Choi says. “I’m interested in how we can make more efficient power circuits to charge the battery in electric vehicles.”
To enhance EV charging, Choi is involved in research on many levels. In addition to advancing the design of spiral coils for high-frequency wireless charging — in which power is transmitted electromagnetically between coils located in a vehicle and charging station — her primary research focuses on designing power circuits that can receive electrical currents at high frequencies from a charging source and transfer the energy to the battery.
[caption id="attachment_34073" align="alignleft" width="418"] UW ECE graduate student Ghovindo Surya turns the knob on an oscilloscope to test the electrical currents received by the power circuit.[/caption]
“We want to have high efficiency,” Choi explains. “When we have 100% power at input and the battery receives only 80% power, then it’s lost as heat. It’s harmful for the system and energy is lost.”
A unique feature of power converters that Choi’s team is working to advance is the two-way flow of energy, which would enable EV batteries to store energy that could be utilized as backup power.
“In an emergency situation, or in case of a blackout, we could draw power from a vehicle into a house,” Choi says.
Learn more about how UW engineering research is driven to advance vehicle electrification on the UW College of Engineering website.
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[post_content] => By Wayne Gillam / UW ECE News
[caption id="attachment_34231" align="alignright" width="575"] UW ECE Associate Professor Sam Burden is part of a multi-institutional research team that examined why walking, running, and jumping are challenging tasks for robots while the same activities appear to be relatively easy for humans and other animals. The team published their findings in a recent issue of the journal Science Robotics. Photo by Nicolas Thomas / Unsplash[/caption]
Over the last few years, millions of people have watched videos of robots walking, running, and jumping with breathtaking power, agility, and speed. However, what many people don’t realize is that these videos are carefully choreographed and take place in tightly controlled environments. In the real world, outside of those controls, legged robots still have a long way to go to match what humans and other animals can do.
It turns out that walking, running, and jumping, or “legged locomotion,” as it’s known in engineering circles, is surprisingly difficult for robots, especially when it comes to achieving dynamic mobility in an uncontrolled environment. Digital, programmable robots have been around for decades now, but compared to animals, their skill at legged locomotion in the real world is barely out of its infancy. That’s not so bad when one considers that animals have had millions of years to evolve and perfect their moves. It even takes a human toddler several years to learn how to walk, run, and jump. So, with those points in mind, perhaps it’s not quite as surprising that it’s taking scientists and engineers a long time to master this difficult skill set on behalf of robots. But why are walking, running, and jumping such challenging tasks for robots, when the same activities seem to be relatively easy for animals?
In a new paper titled, “Why animals can outrun robots,” which was recently published in the journal Science Robotics, a multidisciplinary, multi-institutional research team that included UW ECE Associate Professor Sam Burden examines in depth why this might be.
“If you look at a squirrel, for example, it’s amazing what they can do. And there’s just no comparison at any scale or any kind of modality for legged robots,” Burden said. “The point of this paper is to synthesize across biology and engineering what we know about the components and the whole systems involved and try to answer the question of why animals are so much better at legged locomotion than robots.”
[caption id="attachment_34233" align="alignright" width="350"] UW ECE Associate Professor Sam Burden[/caption]
Burden’s collaborators included Max Donelan, a professor at Simon Fraser University in biomedical physiology and kinesiology; Kaushik Jayaram, an assistant professor in the Paul M. Rady Department of Mechanical Engineering at the University of Colorado Boulder; Simon Sponberg, the Dunn Family Associate Professor of Physics and Biological Sciences at the Georgia Institute of Technology; and Tom Libby, who was a Washington Research Foundation Fellow in Neuroengineering at UW ECE from 2017 to 2019 and is now a senior research engineer at SRI International.
Each researcher in the group explored one of the five engineering subsystems that make up robotic legged locomotion. Together, they dug deep into the scientific literature, investigating and analyzing why animals outperform robots at walking, running, and jumping, and they quantified the differences they found. Before this research, many scientists and engineers believed the main reason animals had a significant advantage over robots was that biological components were superior to engineered parts. But what the team discovered because of their extensive review, was that the opposite was true, and that the whole was far greater than the sum of its parts.
“The way things turned out is that, with only minor exceptions, the engineering subsystems outperform the biological equivalents — and sometimes radically outperform them,” Libby said in a recent press release from Simon Fraser University. “But also, what’s very, very clear is that, if you compare animals to robots at the whole system level, in terms of movement, animals are amazing. And robots have yet to catch up.”
Based on these findings and their intensive examination of engineering subsystems, the team identified in their paper fundamental obstacles that roboticists must overcome to bring robot legged locomotion up to par with humans and other animals. The team also highlighted promising research directions that hold transformative potential to help legged robots achieve animal-level performance.
Engineering subsystems, overcoming obstacles, and promising research directions
The team’s paper was comprehensive in its review of the scientific literature available on this topic. Their research began in 2013 and lasted over a decade, as group members worked on investigation and analysis of legged locomotion in between their other responsibilities.
“In the paper, we divide legged locomotion into five engineering subsystems and cover them all in depth,” Burden said. “Normally, analyzing any single one of these subsystems for either an animal or a robot could be an entire review paper by itself. It’s an ambitious and broad project.”
The five engineering subsystems the team explored were the power system used to store and deliver energy, the frame that provides support and leverage, actuators to modulate mechanical energy, sensors to perceive self and environment, and the control system, which transmits and transforms sensor and actuator signals. For each subsystem, the team compared, contrasted, and quantified differences between legged robots and animals. Burden said that the group wrote this paper primarily for roboticists but that they also wanted their findings to be accessible to biologists to encourage collaboration when tackling the tough problem of improving robotic legged locomotion.
“This paper is rigorously researched, and basically, we’re saying that if you want high performance and want to approach the capabilities of animals, what we need in robotics is an integrative approach. It is not the quality of robotic components that explains this wide performance gap, but rather, how they are put together into a unified whole.” — UW ECE Associate Professor Sam Burden
To that end, the team identified four fundamental obstacles they believe must be overcome to successfully integrate engineered components into more effective robotic systems. Those obstacles are a lack of quantitative metrics for evaluating the many dimensions of legged locomotion; the tradeoffs that arise when subsystems combine and the performance of one component potentially constrains the performance of another; the phenomenon of emergence, where the behavior of the whole system is different from, and irreducible to, the behavior of its component parts; and the very Harry Potter-sounding curse of dimensionality, which means that there is a mind-boggling array of possible component configurations roboticists can choose from when designing legged robots and very little guidance as to which will be the most effective.
To not leave scientists and engineers without paths to solutions, the researchers also identified several promising research directions. Those include systematic comparative studies of multiple animal species, which could reveal generalizable principles that could be applied to robotics; distributing energy, sensing, actuation, and control throughout robot frames, as animals do, which may enhance robustness and advance autonomy; bridging the “sim-to-real” gap with better computational models of robot interactions with the environment; continuing advances in materials used to build robotics, and systematically exploring tradeoffs with respect to multiple performance metrics at both component and system levels.
Overall, the research team emphasized that although further improvements to robotic components are beneficial, the greatest opportunity to improve the performance of legged robots is to make better use of existing parts, much like biological systems do. They advocated in the paper for a more integrated approach to engineering legged robots, taking cues and guidance from biology along the way.
Downstream impacts, ethical considerations, and looking ahead
[caption id="attachment_34245" align="alignright" width="350"] Burden and his colleagues are optimistic that over the long term, when it comes to developing robots that can walk, run, and jump as well as or better than humans and other animals, the benefits will far outweigh the risks. Photo courtesy of the Animal Inspired Movement and Robotics Lab / University of Colorado Boulder[/caption]
By developing a better understanding of the principles involved in legged locomotion for both animals and robots, Burden and his colleagues have moved the field of robotics closer toward a longstanding goal for engineers — creating robots that can walk, run, and jump as well as (and perhaps even better than) humans and other animals. There are many reasons why this is an important, worthy goal. Legged robots with robust agility could perform many useful, and even life-saving, tasks in environments that are hazardous for humans, such as cleaning up after natural and nuclear disasters, disarming bombs, or helping astronauts explore outer space. Principles learned from this robotic development could also be applied to advanced, bio-inspired devices, such as smart prosthetic limbs and exoskeletons. And the potential everyday applications are endless, including developing legged robots to clean the house, do yard work, and even care for the elderly. The automation of various tasks by legged robots across a vast range of industries also promises to substantially enrich the world economy.
But, of course, every powerful technology can be a double-edged sword, and there are some downsides to consider. Robotic automation could enrich the economy, but that will be at the cost of job loss for at least some humans. This could happen in large numbers and at such a rapid pace, it would be hard for society to adjust. The possible weaponization of legged robots also is a serious concern, and some manufacturers are calling on the robotics community and government leaders to take steps to ensure this doesn’t happen. Recently, some thought leaders have suggested that the fear of job loss from robotics is overblown; however, whether or not they are right still remains to be seen. In the meantime, roboticists, industry leaders, and government representatives are exploring different avenues for addressing these sorts of concerns, and that work is ongoing.
Burden and his colleagues are optimistic that over the long term, when it comes to developing robots that can walk, run, and jump as well as or better than humans and other animals, the benefits will far outweigh the risks.
“These are machines that could have a really big, positive impact on people’s lives, but they’re just not capable yet,” Burden said. “This paper is rigorously researched, and basically, we’re saying that if you want high performance and want to approach the capabilities of animals, what we need in robotics is an integrative approach. It is not the quality of robotic components that explains this wide performance gap, but rather, how they are put together into a unified whole.”
Learn more about this research by reading “Why animals can outrun robots” in Science Robotics. More information about UW ECE Associate Professor Sam Burden is available on his bio page.
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UW ECE Associate Professor Sam Burden is part of a multi-institutional research team that examined why walking, running, and jumping are challenging tasks for robots while the same activities appear to be relatively easy for humans and other animals. The team published their findings in a recent issue of the journal Science Robotics. Photo by Nicolas Thomas / Unsplash[/caption]
Over the last few years, millions of people have watched videos of robots walking, running, and jumping with breathtaking power, agility, and speed. However, what many people don’t realize is that these videos are carefully choreographed and take place in tightly controlled environments. In the real world, outside of those controls, legged robots still have a long way to go to match what humans and other animals can do.
It turns out that walking, running, and jumping, or “legged locomotion,” as it’s known in engineering circles, is surprisingly difficult for robots, especially when it comes to achieving dynamic mobility in an uncontrolled environment. Digital, programmable robots have been around for decades now, but compared to animals, their skill at legged locomotion in the real world is barely out of its infancy. That’s not so bad when one considers that animals have had millions of years to evolve and perfect their moves. It even takes a human toddler several years to learn how to walk, run, and jump. So, with those points in mind, perhaps it’s not quite as surprising that it’s taking scientists and engineers a long time to master this difficult skill set on behalf of robots. But why are walking, running, and jumping such challenging tasks for robots, when the same activities seem to be relatively easy for animals?
In a new paper titled, “Why animals can outrun robots,” which was recently published in the journal Science Robotics, a multidisciplinary, multi-institutional research team that included UW ECE Associate Professor Sam Burden examines in depth why this might be.
“If you look at a squirrel, for example, it’s amazing what they can do. And there’s just no comparison at any scale or any kind of modality for legged robots,” Burden said. “The point of this paper is to synthesize across biology and engineering what we know about the components and the whole systems involved and try to answer the question of why animals are so much better at legged locomotion than robots.”
[caption id="attachment_34233" align="alignright" width="350"]
UW ECE Associate Professor Sam Burden[/caption]
Burden’s collaborators included Max Donelan, a professor at Simon Fraser University in biomedical physiology and kinesiology; Kaushik Jayaram, an assistant professor in the Paul M. Rady Department of Mechanical Engineering at the University of Colorado Boulder; Simon Sponberg, the Dunn Family Associate Professor of Physics and Biological Sciences at the Georgia Institute of Technology; and Tom Libby, who was a Washington Research Foundation Fellow in Neuroengineering at UW ECE from 2017 to 2019 and is now a senior research engineer at SRI International.
Each researcher in the group explored one of the five engineering subsystems that make up robotic legged locomotion. Together, they dug deep into the scientific literature, investigating and analyzing why animals outperform robots at walking, running, and jumping, and they quantified the differences they found. Before this research, many scientists and engineers believed the main reason animals had a significant advantage over robots was that biological components were superior to engineered parts. But what the team discovered because of their extensive review, was that the opposite was true, and that the whole was far greater than the sum of its parts.
“The way things turned out is that, with only minor exceptions, the engineering subsystems outperform the biological equivalents — and sometimes radically outperform them,” Libby said in a recent press release from Simon Fraser University. “But also, what’s very, very clear is that, if you compare animals to robots at the whole system level, in terms of movement, animals are amazing. And robots have yet to catch up.”
Based on these findings and their intensive examination of engineering subsystems, the team identified in their paper fundamental obstacles that roboticists must overcome to bring robot legged locomotion up to par with humans and other animals. The team also highlighted promising research directions that hold transformative potential to help legged robots achieve animal-level performance.
Burden and his colleagues are optimistic that over the long term, when it comes to developing robots that can walk, run, and jump as well as or better than humans and other animals, the benefits will far outweigh the risks. Photo courtesy of the Animal Inspired Movement and Robotics Lab / University of Colorado Boulder[/caption]
By developing a better understanding of the principles involved in legged locomotion for both animals and robots, Burden and his colleagues have moved the field of robotics closer toward a longstanding goal for engineers — creating robots that can walk, run, and jump as well as (and perhaps even better than) humans and other animals. There are many reasons why this is an important, worthy goal. Legged robots with robust agility could perform many useful, and even life-saving, tasks in environments that are hazardous for humans, such as cleaning up after natural and nuclear disasters, disarming bombs, or helping astronauts explore outer space. Principles learned from this robotic development could also be applied to advanced, bio-inspired devices, such as smart prosthetic limbs and exoskeletons. And the potential everyday applications are endless, including developing legged robots to clean the house, do yard work, and even care for the elderly. The automation of various tasks by legged robots across a vast range of industries also promises to substantially enrich the world economy.
But, of course, every powerful technology can be a double-edged sword, and there are some downsides to consider. Robotic automation could enrich the economy, but that will be at the cost of job loss for at least some humans. This could happen in large numbers and at such a rapid pace, it would be hard for society to adjust. The possible weaponization of legged robots also is a serious concern, and some manufacturers are calling on the robotics community and government leaders to take steps to ensure this doesn’t happen. Recently, some thought leaders have suggested that the fear of job loss from robotics is overblown; however, whether or not they are right still remains to be seen. In the meantime, roboticists, industry leaders, and government representatives are exploring different avenues for addressing these sorts of concerns, and that work is ongoing.
Burden and his colleagues are optimistic that over the long term, when it comes to developing robots that can walk, run, and jump as well as or better than humans and other animals, the benefits will far outweigh the risks.
“These are machines that could have a really big, positive impact on people’s lives, but they’re just not capable yet,” Burden said. “This paper is rigorously researched, and basically, we’re saying that if you want high performance and want to approach the capabilities of animals, what we need in robotics is an integrative approach. It is not the quality of robotic components that explains this wide performance gap, but rather, how they are put together into a unified whole.”
Learn more about this research by reading “Why animals can outrun robots” in Science Robotics. More information about UW ECE Associate Professor Sam Burden is available on his bio page.
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[post_content] => By Wayne Gillam | UW ECE News
[caption id="attachment_34126" align="alignright" width="575"]
UW ECE alumnus and Affiliate Professor Jai Jaisimha (Ph.D. ‘96) has co-founded a new nonprofit organization, the Transparency Coalition.ai, which is advocating for transparency and regulation of the data used to train artificial intelligence. / Photo by Igor Omilaev, courtesy of the Transparency Coalition.ai[/caption]
Artificial intelligence holds great promise as well as possible peril for society. This rapidly evolving technology stands to accelerate advances in science, engineering, and healthcare as well as improve efficiency and productivity in a vast range of industries. But AI also has serious downsides, which include the potential to spread misinformation and disinformation online, exacerbate algorithmic biases, compromise individual privacy, and even obliterate copyright protections for intellectual property.
It is the peril of AI that drew the attention of UW ECE alumnus and Affiliate Professor Jai Jaisimha (Ph.D. ‘96), who has worked as a technology entrepreneur for decades and has held leadership positions in major tech companies that leverage AI, such as Amazon and Microsoft. Now, along with his co-founder Rob Eleveld, Jaisimha has created a new nonprofit organization, the Transparency Coalition.ai, which seeks to address these concerns by advocating for greater transparency and regulation of the data used to train and inform AI and generative AI models, such as ChatGPT.
“Rob and I were concerned about the rollout of generative AI and how it was going. We were already seeing evidence of societal harm. And we knew that we had the expertise needed to help address some of these issues,” Jaisimha said. “Because of my work in computer vision and imaging when I was at the UW, I spent years studying and understanding pattern recognition, how it worked, and the mathematics behind it. I built early versions of these AI models that are similar to the ones that are out there now.”
[caption id="attachment_34130" align="alignleft" width="250"]
UW ECE alumnus and Affiliate Professor Jai Jaisimha[/caption]
The roots of Jaisimha’s knowledge about AI models and the data used to train them goes back to his time as a doctoral student working with his adviser, UW ECE Professor Emeritus Eve Riskin, who is now the dean of undergraduate education in the electrical and computer engineering department at the Stevens Institute of Technology. With oversight by Riskin, Jaisimha applied statistical pattern recognition techniques to better understand datasets and how to use them to make online browsing a more interactive and personalized experience. During this time, he also had an internship at a startup that did research for government agencies, which taught him the importance of data curation as well as algorithmic model construction, testing and validation.
These experiences as a student carried over into his professional life, which has been defined by his entrepreneurial ventures and corporate leadership.
“When you’re building a company, it’s not just about making a cool demo,” Jaisimha said. “It’s about making sure you have the entire pipeline of AI model building in place: data collection, data cleansing, being rigorous about validating and testing your results, and automating performance monitoring. That way, you end up building a robust system. Those are all things I learned at UW ECE.”
UW ECE Assistant Professor Jungwon Choi's research focuses on designing power circuits that can receive electrical currents at high frequencies from a charging source and transfer the energy to the battery. Shown above, Choi with UW ECE graduate student Manas Palmal.[/caption]
Adapted from an article by Brooke Fisher, Photos by Dennis Wise | UW College of Engineering
Imagine rolling into a parking spot and your electric vehicle (EV) automatically begins to charge, quickly and without cables, thanks to a compact charging station on the ground. UW ECE Assistant Professor Jungwon Choi can do more than envision it — she’s developing the technology.
“Charging time is a barrier for people buying EVs,” Choi says. “I’m interested in how we can make more efficient power circuits to charge the battery in electric vehicles.”
UW ECE graduate student Ghovindo Surya turns the knob on an oscilloscope to test the electrical currents received by the power circuit.[/caption]
“We want to have high efficiency,” Choi explains. “When we have 100% power at input and the battery receives only 80% power, then it’s lost as heat. It’s harmful for the system and energy is lost.”
A unique feature of power converters that Choi’s team is working to advance is the two-way flow of energy, which would enable EV batteries to store energy that could be utilized as backup power.
“In an emergency situation, or in case of a blackout, we could draw power from a vehicle into a house,” Choi says.
Learn more about how UW engineering research is driven to advance vehicle electrification on the UW College of Engineering website.
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