TL;DR
- University of Wollongong (UOW) researchers have mimicked the supercoiling properties of DNA to develop a new type of artificial muscle for use in miniature robot applications. Their research is published in Science Robotics.
- Someday, scientists believe, tiny DNA-based robots and other nanodevices will deliver medicine inside our bodies, detect the presence of deadly pathogens, and help manufacture increasingly smaller electronics. Researchers took a big step toward that future by developing a new tool that can design much more complex DNA robots and nanodevices than were ever possible before in a fraction of the time.
- Researchers at Hong Kong University of Science and Technology recently developed a computer vision-based robotic foot with tactile sensing capabilities. When integrated at the end of a robot’s legs, the artificial foot can increase a robot’s balance and stability during locomotion.
- The field of soft robotics has exploded in the past decade, as ever more researchers seek to make real the potential of these pliant, flexible automata in a variety of realms, including search and rescue, exploration and medicine. For all the excitement surrounding these new machines, however, UC Santa Barbara mechanical engineering professor Elliot Hawkes wants to ensure that soft robotics research is more than just a flash in the pan. “Some new, rapidly growing fields never take root, while others become thriving disciplines,” Hawkes said.
- Ever wondered why your virtual home assistant doesn’t understand your questions? Or why your navigation app took you on the side street instead of the highway? Researchers have now designed a robot that ‘thinks out loud’ so that users can hear its thought process and better understand the robot’s motivations and decisions.
- Although robotic devices are used in everything from assembly lines to medicine, engineers have a hard time accounting for the friction that occurs when those robots grip objects — particularly in wet environments. Researchers have now discovered a new law of physics that accounts for this type of friction, which should advance a wide range of robotic technologies.
- Researchers have developed a new, high-performance artificial muscle technology. The new technology enables more human-like motion due to its flexibility and adaptability, but outperforms human skeletal muscle in several metrics.
- As artificial intelligence has attracted interest, researchers are focused on understanding how the brain accomplishes cognition so they can construct systems with general intelligence comparable to humans’ intelligence. Researchers propose an approach to AI that focuses on integrating photonic components with superconducting electronics; using light for communication and complex electronic circuits for computation could enable artificial cognitive systems of scale and functionality beyond what can be achieved with either light or electronics alone.
- Last week’s CMU RI Seminar is by Avik De from Ghost Robotics, on “Design and control of insect-scale bees and dog-scale quadrupeds.”
- With the current pandemic accelerating the revolution of AI in healthcare, where is the industry heading in the next 5–10 years? What are the key challenges and most exciting opportunities? These questions are answered by HAI’s Co-Director, Fei-Fei Li and the Founder of DeepLearning.AI, Andrew Ng in the fireside chat virtual event recording.
- Check out robotics upcoming events. And more!
Robotics market
The global market for robots is expected to grow at a compound annual growth rate (CAGR) of around 26 percent to reach just under 210 billion U.S. dollars by 2025.
Size of the global market for industrial and non-industrial robots between 2018 and 2025 (in billion U.S. dollars):
Size of the global market for industrial and non-industrial robots between 2018 and 2025 (in billion U.S. dollars). Source: Statista
Latest News & Researches
Dual high-stroke and high–work capacity artificial muscles inspired by DNA supercoiling
by G.M. Spinks el al. in Science Robotics
University of Wollongong (UOW) researchers have mimicked the supercoiling properties of DNA to develop a new type of artificial muscle for use in miniature robot applications. Their research is published today in Science Robotics.
One of the challenges to the miniaturization of robotics technology, such as developing micro-tools for remote robotic surgery, is that conventional mechanical drive systems (or “actuators”) are difficult to downsize without loss of performance. Artificial muscles that generate large and reversible movement, high mechanical work output, respond quickly and last for millions of cycles would be ideally suited for miniature machines, said the study’s lead author, Professor Geoffrey Spinks from UOW’s Australian Institute for Innovative Materials.
“The miniaturization of robotic devices will have many applications, but the main challenge is how to generate powerful movement and forces in tiny devices,” Professor Spinks said. “Electric motors are simply too complicated to downsize, so we look to artificial muscles to provide compact mechanical actuation. Arrays of miniature artificial muscles could be combined to fabricate advanced prosthetics and wearable devices to help people move when they have a physical disability or injury. Tiny actuators can also be incorporated into tools for non-invasive surgery and micro-manipulators in industry.”
The inspiration for this new type of artificial muscle came from nature. To pack into the cell nucleus, DNA must contract by more than 1000 times, in part via a process called supercoiling.
“Our work describes a new type of artificial muscle that mimics the way that DNA molecules collapse when packing into the cell nucleus,” Professor Spinks said. “We were able to create DNA-like unwinding by swelling twisted fibers. Supercoiling occurred when the fiber ends were blocked against rotation. We show that these new artificial muscles generate a large amount of mechanical work.”
The research team optimized the fibers through modeling to maximize stroke and work output, and downsized the fibers to decrease their response time. They then successfully trialed the new muscles on possible applications, including micro-scissors and micro-tweezers.
Co-author Dr. Sina Naficy, now at the University of Sydney, said, “Seeing what happens in the natural world and being able to mimic those actions in a synthetic system is very interesting. We have learned that forming fiber composites where the fiber is wound into a helix provides a convenient way to store and release mechanical energy. There are many examples of these kinds of helical composites in nature, from DNA molecules to plant tendrils. These systems offer exciting prospects for future developments.”
The action of the new muscles is quite slow, limiting their application at present, so the next challenge is to speed up the response, according to Dr. Javad Foroughi from UOW’s Faculty of Engineering and Information Sciences, another co-author of the research paper.
“We have used hydrogels to generate the volume changes that drive the supercoiling but that response is inherently slow,” Dr. Foroughi said. “We do believe that the speed can be increased by making smaller diameter fibers, but right now, the applications are limited to those that need a slower response,” Professor Spinks said. “Developing faster supercoiling muscles would open up further applications. We hope that others will explore different means for generating a volume change — such as by electrical heating — that can lead to a faster response.”
Integrated computer-aided engineering and design for DNA assemblies
by Chao-Min Huang, Anjelica Kucinic, Joshua A. Johnson, Hai-Jun Su, Carlos E. Castro in Nature Materials
Someday, scientists believe, tiny DNA-based robots and other nanodevices will deliver medicine inside our bodies, detect the presence of deadly pathogens, and help manufacture increasingly smaller electronics. Researchers took a big step toward that future by developing a new tool that can design much more complex DNA robots and nanodevices than were ever possible before in a fraction of the time.
In a paper published in the journal Nature Materials, researchers from The Ohio State University — led by former engineering doctoral student Chao-Min Huang — unveiled new software they call MagicDNA.
The software helps researchers design ways to take tiny strands of DNA and combine them into complex structures with parts like rotors and hinges that can move and complete a variety of tasks, including drug delivery.
Researchers have been doing this for a number of years with slower tools with tedious manual steps, said Carlos Castro, co-author of the study and associate professor of mechanical and aerospace engineering at Ohio State.
“But now, nanodevices that may have taken us several days to design before now take us just a few minutes,” Castro said.
And now researchers can make much more complex — and useful — nanodevices.
“Previously, we could build devices with up to about six individual components and connect them with joints and hinges and try to make them execute complex motions,” said study co-author Hai-Jun Su, professor of mechanical and aerospace engineering at Ohio State. “With this software, it is not hard to make robots or other devices with upwards of 20 components that are much easier to control. It is a huge step in our ability to design nanodevices that can perform the complex actions that we want them to do.”
The software has a variety of advantages that will help scientists design better, more helpful nanodevices and — researchers hope — shorten the time before they are in everyday use.
One advantage is that it allows researchers to carry out the entire design truly in 3D. Earlier design tools only allowed creation in 2D, forcing researchers to map their creations into 3D. That meant designers couldn’t make their devices too complex.
The software also allows designers to build DNA structures “bottom up” or “top down.” In “bottom up” design, researchers take individual strands of DNA and decide how to organize them into the structure they want, which allows fine control over local device structure and properties. But they can also take a “top down” approach where they decide how their overall device needs to be shaped geometrically and then automate how the DNA strands are put together. Combining the two allows for increasing complexity of the overall geometry while maintaining precise control over individual component properties, Castro said.
Another key element of the software is that it allows simulations of how designed DNA devices would move and operate in the real world.
“As you make these structures more complex, it is difficult to predict exactly what they are going to look like and how they are going to behave,” Castro said. “It is critical to be able to simulate how our devices will actually operate. Otherwise, we waste a lot of time.”
As a demonstration of the software’s ability, co-author Anjelica Kucinic, a doctoral student in chemical and biomolecular engineering at Ohio State, led the researchers in making and characterizing many nanostructures designed by the software.
Some of the devices they created included robot arms with claws that can pick up smaller items, and a hundred nanometer-sized structure that looks like an airplane (The “airplane” is 1000 times smaller than the width of a human hair). The ability to make more complex nanodevices means that they can do more useful things and even carry out multiple tasks with one device, Castro said. For example, it is one thing to have a DNA robot that, after injection into the bloodstream, can detect a certain pathogen.
“But a more complex device may not only detect that something bad is happening, but can also react by releasing a drug or capturing the pathogen,” he said. “We want to be able to design robots that respond in a particular way to a stimulus or move in a certain way.”
Castro said he expects that for the next few years, the MagicDNA software will be used at universities and other research labs. But its use could expand in the future.
“There is getting to be more and more commercial interest in DNA nanotechnology,” he said. “I think in the next five to 10 years we will start seeing commercial applications of DNA nanodevices and we are optimistic that this software can help drive that.”
Hard questions for soft robotics
by Elliot W. Hawkes, Carmel Majidi, Michael T. Tolley in Science Robotics
The field of soft robotics has exploded in the past decade, as ever more researchers seek to make real the potential of these pliant, flexible automata in a variety of realms, including search and rescue, exploration and medicine.
For all the excitement surrounding these new machines, however, UC Santa Barbara mechanical engineering professor Elliot Hawkes wants to ensure that soft robotics research is more than just a flash in the pan. “Some new, rapidly growing fields never take root, while others become thriving disciplines,” Hawkes said.
To help guarantee the longevity of soft robotics research, Hawkes, whose own robots have garnered interest for their bioinspired and novel locomotion and for the new possibilities they present, offers an approach that moves the field forward. His viewpoint, written with colleagues Carmel Majidi from Carnegie Mellon University and Michael T. Tolley of UC San Diego, is published in the journal Science Robotics.
“We were looking at publication data for soft robotics and noticed a phase of explosive growth over the last decade,” Hawkes said. “We became curious about trends like this in new fields, and how new fields take root.”
The first decade of widespread soft robotics research, according to the group, “was characterized by defining, inspiring and exploring,” as roboticists took to heart what it meant to create a soft robot, from materials systems to novel ways of navigating through and interacting with the environment.
However, the researchers argue, “for soft robotics to become a thriving, impactful field in the next decade, every study must make a meaningful contribution.” According to Hawkes, the long-term duration of a rapidly growing field is often a matter of whether the initial exploratory research matures.
With that in mind, the group presents a three-tiered categorization system to apply to future soft robotics work.
“The three-tier system categorizes studies within the field, not the field as a whole,” Hawkes explained. “For example, there will be articles coming out this year that will be Level 0, Level 1 and Level 2. The goal is to push as many Level 0 studies toward Level 1 and Level 2.”
From Baseline to Broad Contribution
“Soft for soft’s sake” could be used to characterize Level 0 in the categorization system, as researchers have, for the past decade, rapidly and broadly explored new materials and mechanisms that could fall under the notion of “soft robot.” While these studies were necessary to define the field, according to the authors, maintaining research at this level puts soft robotics at the risk of stagnation.
With the benefits of a solid foundation, present and future roboticists are now encouraged to identify areas for performance improvement and solutions to gaps in the knowledge of soft robotics — the hallmark of Level 1. These studies will push the field forward, the researchers said, as novel results could elevate technological performance of soft systems.
However, they say, “whenever possible, we should strive to push beyond work that only contributes to our field.” Studies in the Level 2 category go beyond soft robotics to become applications in the broader field of engineering. Here, softness is more than an artificial constraint, according to the paper; rather, it “advances state-of-the art technology and understanding across disciplines” and may even displace long-used conventional technologies.
One way to move beyond Level 0 lies in the training of the next generation of roboticists, the researchers said. Consolidating the best available knowledge contributed by previous work will prime those just entering the field to “ask the right questions” as they pursue their research.
“We hope that the categorization we offer will serve the field as a tool to help improve contribution, ideally increasing the impact of soft robotics in the coming decade,” Hawkes said.
A tactile sensing foot for single robot leg stabilization
by Guanlan Zhang, Yipai Du, Yazhan Zhan, Michael Yu Wang
In order to effectively navigate real-world environments, legged robots should be able to move swiftly and freely while maintaining their balance. This is particularly true for humanoid robots, robots with two legs and a human-like body structure. Building robots that are stable on their legs while walking can be challenging. In fact, legged robots typically have unstable dynamics, due to their pendulum-like structure. Researchers at Hong Kong University of Science and Technology recently developed a computer vision-based robotic foot with tactile sensing capabilities. When integrated at the end of a robot’s legs, the artificial foot can increase a robot’s balance and stability during locomotion.
“Our recent paper focuses on the application of vision-based tactile sensing on legged robots,” Guanlan Zhang, one of the researchers who carried out the study, “It is based on the idea that tactile/haptic sensing plays an important role in human interaction with the environment.”
The overall objective of the recent study by Zhang and Yipai Du, under the guidance of their advisor Professor Michael Y. Wang at HKUST Robotics Institute, was to develop robots that can sense surfaces while completing tasks within a given environment, just as humans would. More specifically, they wanted to allow robots to balance their legs by sensing the ground beneath them. To achieve this, they inserted a soft, artificial “skin” under their robotic foot and installed a camera inside it, just above the “skin.”
“We deliberately painted special patterns on the inside of the skin, and the camera we used can capture this pattern,” Zhang explained. “As the foot touches the ground, the soft skin will deform due to external forces. The pattern will also deform, and through the deformation of the pattern, we are able to obtain contact information such as the degree of contact angle between the foot and the ground and tilting of the leg.”
The artificial foot developed by the researchers can collect far richer information about the surface a robot is walking on than conventional sensors. This information can then be used to improve a robot’s stability in scenarios where balancing systems based on traditional sensors might fail or perform poorly.
To convert images collected by the foot into contact-related data, the researchers used a new deep learning framework they developed. Subsequently, they carried out tests to evaluate the stability of a robotic leg with the foot integrated in it. They found that the foot could successfully estimate both the tilting angle of the surface beneath it and the foot’s pose.
In addition, Zhang and his colleagues carried out a series of experiments to test the overall feasibility and effectiveness of the tactile robotic system they created. Their system significantly outperformed conventional single-legged robotic systems, enabling greater balance and stability.
“During our experiments, we found that the information contained in the contact phenomenon is more than we expected,” Zhang said. “We thus abandoned some redundant knowledge obtained by the sensor. However, high-level information, such as events (slip, collision, etc.) may also be detected or predicted by the tactile sensing foot.”
In the future, the robotic foot created by this team of researchers could be used to develop legged robots that can maintain their stability when walking on different terrains and surfaces. In addition, it could enable more complex leg movements and locomotion styles in humanoid robots.
“In the future, we would like to apply our sensor on a real legged robot and conduct experiments related to robot-environment interaction,” Zhang said. “We want to focus on how the tactile information is related to some events in locomotion, such as slip. And how to make use of this information in robot control.”
What robots want? Hearing the inner voice of a robot
by Arianna Pipitone, Antonio Chella in iScience
Ever wondered why your virtual home assistant doesn’t understand your questions? Or why your navigation app took you on the side street instead of the highway? In a new study, Italian researchers designed a robot that “thinks out loud” so that users can hear its thought process and better understand the robot’s motivations and decisions.
“If you were able to hear what the robots are thinking, then the robot might be more trustworthy,” says co-author Antonio Chella, describing first author Arianna Pipitone’s idea that launched the study at the University of Palermo. “The robots will be easier to understand for laypeople, and you don’t need to be a technician or engineer. In a sense, we can communicate and collaborate with the robot better.”
Inner speech is common in people and can be used to gain clarity, seek moral guidance, and evaluate situations in order to make better decisions. To explore how inner speech might impact a robot’s actions, the researchers built a robot called Pepper that speaks to itself. They then asked people to set the dinner table with Pepper according to etiquette rules to study how Pepper’s self-dialogue skills influence human-robot interactions.
The scientists found that, with the help of inner speech, Pepper is better at solving dilemmas. In one experiment, the user asked Pepper to place the napkin at the wrong spot, contradicting the etiquette rule. Pepper started asking itself a series of self-directed questions and concluded that the user might be confused. To be sure, Pepper confirmed the user’s request, which led to further inner speech.
“Ehm, this situation upsets me. I would never break the rules, but I can’t upset him, so I’m doing what he wants,” Pepper said to itself, placing the napkin at the requested spot. Through Pepper’s inner voice, the user can trace its thoughts to learn that Pepper was facing a dilemma and solved it by prioritizing the human’s request. The researchers suggest that the transparency could help establish human-robot trust.
Comparing Pepper’s performance with and without inner speech, Pipitone and Chella discovered that the robot had a higher task-completion rate when engaging in self-dialogue. Thanks to inner speech, Pepper outperformed the international standard functional and moral requirements for collaborative robots — guidelines that machines, from humanoid AI to mechanic arms at the manufacturing line, follow.
“People were very surprised by the robot’s ability,” says Pipitone. “The approach makes the robot different from typical machines because it has the ability to reason, to think. Inner speech enables alternative solutions for the robots and humans to collaborate and get out of stalemate situations.”
Although hearing the inner voice of robots enriches the human-robot interaction, some people might find it inefficient because the robot spends more time completing tasks when it talks to itself. The robot’s inner speech is also limited to the knowledge that researchers gave it. Still, Pipitone and Chella say their work provides a framework to further explore how self-dialogue can help robots focus, plan, and learn.
“In some sense, we are creating a generational robot that likes to chat,” says Chella. The authors say that, from navigation apps and the camera on your phone to medical robots in the operation rooms, machines and computers alike can benefit from this chatty feature. “Inner speech could be useful in all the cases where we trust the computer or a robot for the evaluation of a situation,” Chella says.
Elastohydrodynamic friction of robotic and human fingers on soft micropatterned substrates
by Yunhu Peng, Christopher M. Serfass, Anzu Kawazoe, Yitian Shao, Kenneth Gutierrez, Catherine N. Hill, Veronica J. Santos, Yon Visell, Lilian C. Hsiao in Nature Materials
Although robotic devices are used in everything from assembly lines to medicine, engineers have a hard time accounting for the friction that occurs when those robots grip objects — particularly in wet environments. Researchers have now discovered a new law of physics that accounts for this type of friction, which should advance a wide range of robotic technologies.
“Our work here opens the door to creating more reliable and functional haptic and robotic devices in applications such as telesurgery and manufacturing,” says Lilian Hsiao, an assistant professor of chemical and biomolecular engineering at North Carolina State University and corresponding author of a paper on the work.
At issue is something called elastohydrodynamic lubrication (EHL) friction, which is the friction that occurs when two solid surfaces come into contact with a thin layer of fluid between them. This would include the friction that occurs when you rub your fingertips together, with the fluid being the thin layer of naturally occurring oil on your skin. But it could also apply to a robotic claw lifting an object that has been coated with oil, or to a surgical device that is being used inside the human body.
One reason friction is important is because it helps us hold things without dropping them.
“Understanding friction is intuitive for humans — even when we’re handling soapy dishes,” Hsiao says. “But it is extremely difficult to account for EHL friction when developing materials that controls grasping capabilities in robots.”
To develop materials that help control EHL friction, engineers would need a framework that can be applied uniformly to a wide variety of patterns, materials and dynamic operating conditions. And that is exactly what the researchers have discovered.
“This law can be used to account for EHL friction, and can be applied to many different soft systems — as long as the surfaces of the objects are patterned,” Hsiao says.
In this context, surface patterns could be anything from the slightly raised surfaces on the tips of our fingers to grooves in the surface of a robotic tool.
The new physical principle, developed jointly by Hsiao and her graduate student Yunhu Peng, makes use of four equations to account for all of the physical forces at play in understanding EHL friction. In the paper, the research team demonstrated the law in three systems: human fingers; a bio-inspired robotic fingertip; and a tool called a tribo-rheometer, which is used to measure frictional forces. Peng is first author of the paper.
“These results are very useful in robotic hands that have more nuanced controls for reliably handling manufacturing processes,” Hsiao says. “And it has obvious applications in the realm of telesurgery, in which surgeons remotely control robotic devices to perform surgical procedures. We view this as a fundamental advancement for understanding touch and for controlling touch in synthetic systems.”
Optoelectronic intelligence
by Jeffrey M. Shainline in Applied Physics Letters
As artificial intelligence has attracted broad interest, researchers are focused on understanding how the brain accomplishes cognition so they can construct artificial systems with general intelligence comparable to humans’ intelligence.
Many have approached this challenge by using conventional silicon microelectronics in conjunction with light. However, the fabrication of silicon chips with electronic and photonic circuit elements is difficult for many physical and practical reasons related to the materials used for the components.
Researchers at the National Institute of Standards and Technology propose an approach to large-scale artificial intelligence that focuses on integrating photonic components with superconducting electronics rather than semiconducting electronics.
“We argue that by operating at low temperature and using superconducting electronic circuits, single-photon detectors, and silicon light sources, we will open a path toward rich computational functionality and scalable fabrication,” said author Jeffrey Shainline.
Using light for communication in conjunction with complex electronic circuits for computation could enable artificial cognitive systems of scale and functionality beyond what can be achieved with either light or electronics alone.
“What surprised me most was that optoelectronic integration may be much easier when working at low temperatures and using superconductors than when working at room temperatures and using semiconductors,” said Shainline.
Superconducting photon detectors enable detection of a single photon, while semiconducting photon detectors require about 1,000 photons. So not only do silicon light sources work at 4 kelvins, but they also can be 1,000 times less bright than their room temperature counterparts and still communicate effectively.
Some applications, such as chips in cellphones, require working at room temperature, but the proposed technology would still have wide reaching applicability for advanced computing systems.
The researchers plan to explore more complex integration with other superconducting electronic circuits as well as demonstrate all the components that comprise artificial cognitive systems, including synapses and neurons.
Showing that the hardware can be manufactured in a scalable manner, so large systems can be realized at a reasonable cost, will also be important. Superconducting optoelectronic integration could also help create scalable quantum technologies based on superconducting or photonic qubits. Such quantum-neural hybrid systems may also lead to new ways of leveraging the strengths of quantum entanglement with spiking neurons.
Cavatappi artificial muscles from drawing, twisting, and coiling polymer tubes
by Diego R. Higueras-Ruiz, Michael W. Shafer, Heidi P. Feigenbaum in Science Robotics
In the field of robotics, researchers are continually looking for the fastest, strongest, most efficient and lowest-cost ways to actuate, or enable, robots to make the movements needed to carry out their intended functions.
The quest for new and better actuation technologies and ‘soft’ robotics is often based on principles of biomimetics, in which machine components are designed to mimic the movement of human muscles — and ideally, to outperform them. Despite the performance of actuators like electric motors and hydraulic pistons, their rigid form limits how they can be deployed. As robots transition to more biological forms and as people ask for more biomimetic prostheses, actuators need to evolve.
Associate professor (and alum) Michael Shafer and professor Heidi Feigenbaum of Northern Arizona University’s Department of Mechanical Engineering, along with graduate student researcher Diego Higueras-Ruiz, published a paper presenting a new, high-performance artificial muscle technology they developed in NAU’s Dynamic Active Systems Laboratory. The paper details how the new technology enables more human-like motion due to its flexibility and adaptability, but outperforms human skeletal muscle in several metrics.
“We call these new linear actuators cavatappi artificial muscles based on their resemblance to the Italian pasta,” Shafer said.
Because of their coiled, or helical, structure, the actuators can generate more power, making them an ideal technology for bioengineering and robotics applications. In the team’s initial work, they demonstrated that cavatappi artificial muscles exhibit specific work and power metrics ten and five times higher than human skeletal muscles, respectively, and as they continue development, they expect to produce even higher levels of performance.
“The cavatappi artificial muscles are based on twisted polymer actuators (TPAs), which were pretty revolutionary when they first came out because they were powerful, lightweight and cheap. But they were very inefficient and slow to actuate because you had to heat and cool them. Additionally, their efficiency is only about two percent,” Shafer said. “For the cavatappi, we get around this by using pressurized fluid to actuate, so we think these devices are far more likely to be adopted. These devices respond about as fast as we can pump the fluid. The big advantage is their efficiency. We have demonstrated contractile efficiency of up to about 45 percent, which is a very high number in the field of soft actuation.”
The engineers think this technology could be used in soft robotics applications, conventional robotic actuators (for example, for walking robots), or even potentially in assistive technologies like exoskeletons or prostheses.
“We expect that future work will include the use of cavatappi artificial muscles in many applications due to their simplicity, low-cost, lightweight, flexibility, efficiency and strain energy recovery properties, among other benefits,” Shafer said.
Technology is available for licensing, partnering opportunities.
Working with the NAU Innovations team, the inventors have taken steps to protect their intellectual property. The technology has entered the protection and early commercialization stage and is available for licensing and partnering opportunities. For more information, please contact NAU Innovations.
Videos
Ingenuity’s third flight achieved a longer flight time and more sideways movement than previously attempted. During the 80-second flight, the helicopter climbed to 16 feet (5 meters) and flew 164 feet (50 meters) downrange and back, for a total distance of 328 feet (100 meters). The third flight test took place at “Wright Brothers Field” in Jezero Crater, Mars, on April 25, 2021.
Last week’s CMU RI Seminar is by Avik De from Ghost Robotics, on “Design and control of insect-scale bees and dog-scale quadrupeds.”
With the current pandemic accelerating the revolution of AI in healthcare, where is the industry heading in the next 5–10 years? What are the key challenges and most exciting opportunities? These questions are answered by HAI’s Co-Director, Fei-Fei Li and the Founder of DeepLearning.AI, Andrew Ng in the fireside chat virtual event recording.
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