Why can't robots outrun animals?

Robotics engineers have worked for decades and invested many millions of research dollars in attempts to create a robot that can walk or run as well as an animal. And yet, it remains the case that many animals are capable of feats that would be impossible for robots that exist today.

"A wildebeest can migrate for thousands of kilometres over rough terrain, a mountain goat can climb up a literal cliff, finding footholds that don't even seem to be there, and cockroaches can lose a leg and not slow down," says Dr. Max Donelan, Professor in Simon Fraser University's Department of Biomedical Physiology and Kinesiology. "We have no robots capable of anything like this endurance, agility and robustness."

To understand why, and quantify how, robots lag behind animals, an interdisciplinary team of scientists and engineers from leading research universities completed a detailed study of various aspects of running robots, comparing them with their equivalents in animals, for a paper published in Science Robotics. The paper finds that, by the metrics engineers use, biological components performed surprisingly poorly compared to fabricated parts. Where animals excel, though, is in their integration and control of those components.

Alongside Donelan, the team comprised Drs. Sam Burden, Associate Professor in the Department of Electrical & Computer Engineering at the University of Washington; Tom Libby, Senior Research Engineer, SRI International; Kaushik Jayaram, Assistant Professor in the Paul M Rady Department of Mechanical Engineering at the University of Colorado Boulder; and Simon Sponberg, Dunn Family Associate Professor of Physics and Biological Sciences at the Georgia Institute of Technology.

The researchers each studied one of five different "subsystems" that combine to create a running robot -- Power, Frame, Actuation, Sensing, and Control -- and compared them with their biological equivalents. Previously, it was commonly accepted that animals' outperformance of robots must be due to the superiority of biological components.

"The way things turned out is that, with only minor exceptions, the engineering subsystems outperform the biological equivalents -- and sometimes radically outperformed them," says Libby. "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."

More optimistically for the field of robotics, the researchers noted that, if you compare the relatively short time that robotics has had to develop its technology with the countless generations of animals that have evolved over many millions of years, the progress has actually been remarkably quick.

"It will move faster, because evolution is undirected," says Burden. "Whereas we can very much correct how we design robots and learn something in one robot and download it into every other robot, biology doesn't have that option. So there are ways that we can move much more quickly when we engineer robots than we can through evolution -- but evolution has a massive head start."

More than simply an engineering challenge, effective running robots offer countless potential uses. Whether solving 'last mile' delivery challenges in a world designed for humans that is often difficult to navigate for wheeled robots, carrying out searches in dangerous environments or handling hazardous materials, there are many potential applications for the technology.

Read more at Science Daily

Two artificial intelligences talk to each other

Performing a new task based solely on verbal or written instructions, and then describing it to others so that they can reproduce it, is a cornerstone of human communication that still resists artificial intelligence (AI). A team from the University of Geneva (UNIGE) has succeeded in modelling an artificial neural network capable of this cognitive prowess. After learning and performing a series of basic tasks, this AI was able to provide a linguistic description of them to a ''sister'' AI, which in turn performed them. These promising results, especially for robotics, are published in Nature Neuroscience.

Performing a new task without prior training, on the sole basis of verbal or written instructions, is a unique human ability.

What's more, once we have learned the task, we are able to describe it so that another person can reproduce it. This dual capacity distinguishes us from other species which, to learn a new task, need numerous trials accompanied by positive or negative reinforcement signals, without being able to communicate it to their congeners.

A sub-field of artificial intelligence (AI) -- Natural language processing -- seeks to recreate this human faculty, with machines that understand and respond to vocal or textual data.

This technique is based on artificial neural networks, inspired by our biological neurons and by the way they transmit electrical signals to each other in the brain.

However, the neural calculations that would make it possible to achieve the cognitive feat described above are still poorly understood.

''Currently, conversational agents using AI are capable of integrating linguistic information to produce text or an image.

But, as far as we know, they are not yet capable of translating a verbal or written instruction into a sensorimotor action, and even less explaining it to another artificial intelligence so that it can reproduce it,'' explains Alexandre Pouget, full professor in the Department of Basic Neurosciences at the UNIGE Faculty of Medicine.

A model brain

The researcher and his team have succeeded in developing an artificial neuronal model with this dual capacity, albeit with prior training.

''We started with an existing model of artificial neurons, S-Bert, which has 300 million neurons and is pre-trained to understand language.

We 'connected' it to another, simpler network of a few thousand neurons,'' explains Reidar Riveland, a PhD student in the Department of Basic Neurosciences at the UNIGE Faculty of Medicine, and first author of the study.

In the first stage of the experiment, the neuroscientists trained this network to simulate Wernicke's area, the part of our brain that enables us to perceive and interpret language.

In the second stage, the network was trained to reproduce Broca's area, which, under the influence of Wernicke's area, is responsible for producing and articulating words.

The entire process was carried out on conventional laptop computers.

Written instructions in English were then transmitted to the AI.

For example: pointing to the location -- left or right -- where a stimulus is perceived; responding in the opposite direction of a stimulus; or, more complex, between two visual stimuli with a slight difference in contrast, showing the brighter one.

The scientists then evaluated the results of the model, which simulated the intention of moving, or in this case pointing.

''Once these tasks had been learned, the network was able to describe them to a second network -- a copy of the first -- so that it could reproduce them.

To our knowledge, this is the first time that two AIs have been able to talk to each other in a purely linguistic way,'' says Alexandre Pouget, who led the research.

Read more at Science Daily

Robotic drug capsule can deliver drugs to gut

One reason that it's so difficult to deliver large protein drugs orally is that these drugs can't pass through the mucus barrier that lines the digestive tract. This means that insulin and most other "biologic drugs" -- drugs consisting of proteins or nucleic acids -- have to be injected or administered in a hospital.

A new drug capsule developed at MIT may one day be able to replace those injections. The capsule has a robotic cap that spins and tunnels through the mucus barrier when it reaches the small intestine, allowing drugs carried by the capsule to pass into cells lining the intestine.

"By displacing the mucus, we can maximize the dispersion of the drug within a local area and enhance the absorption of both small molecules and macromolecules," says Giovanni Traverso, the Karl van Tassel Career Development Assistant Professor of Mechanical Engineering at MIT and a gastroenterologist at Brigham and Women's Hospital.

In a study appearing today in Science Robotics, the researchers demonstrated that they could use this approach to deliver insulin as well as vancomycin, an antibiotic peptide that currently has to be injected.

Shriya Srinivasan, a research affiliate at MIT's Koch Institute for Integrative Cancer Research and a junior fellow at the Society of Fellows at Harvard University, is the lead author of the study.

Tunneling through

For several years, Traverso's lab has been developing strategies to deliver protein drugs such as insulin orally. This is a difficult task because protein drugs tend to be broken down in acidic environment of the digestive tract, and they also have difficulty penetrating the mucus barrier that lines the tract.

To overcome those obstacles, Srinivasan came up with the idea of creating a protective capsule that includes a mechanism that can tunnel through mucus, just as tunnel boring machines drill into soil and rock.

"I thought that if we could tunnel through the mucus, then we could deposit the drug directly on the epithelium," she says. "The idea is that you would ingest this capsule and the outer layer would dissolve in the digestive tract, exposing all these features that start to churn through the mucus and clear it."

The "RoboCap" capsule, which is about the size of a multivitamin, carries its drug payload in a small reservoir at one end and carries the tunnelling features in its main body and surface. The capsule is coated with gelatin that can be tuned to dissolve at a specific pH.

When the coating dissolves, the change in pH triggers a tiny motor inside the RoboCap capsule to start spinning. This motion helps the capsule to tunnel into the mucus and displace it. The capsule is also coated with small studs that brush mucus away, similar to the action of a toothbrush.

The spinning motion also helps to erode the compartment that carries the drug, which is gradually released into the digestive tract.

"What the RoboCap does is transiently displace the initial mucus barrier and then enhance absorption by maximizing the dispersion of the drug locally," Traverso says. "By combining all of these elements, we're really maximizing our capacity to provide the optimal situation for the drug to be absorbed."

Enhanced delivery

In tests in animals, the researchers used this capsule to deliver either insulin or vancomycin, a large peptide antibiotic that is used to treat a broad range of infections, including skin infections as well as infections affecting orthopedic implants. With the capsule, the researchers found that they could deliver 20 to 40 times more drug than a similar capsule without the tunneling mechanism.

Once the drug is released from the capsule, the capsule itself passes through the digestive tract on its own. The researchers found no sign of inflammation or irritation in the digestive tract after the capsule passed through, and they also observed that the mucus layer reforms within a few hours after being displaced by the capsule.

Another approach that some researchers have used to enhance oral delivery of drugs is to give them along with additional drugs that help them cross through the intestinal tissue. However, these enhancers often only work with certain drugs. Because the MIT team's new approach relies solely on mechanical disruptions to the mucus barrier, it could potentially be applied to a broader set of drugs, Traverso says.

"Some of the chemical enhancers preferentially work with certain drug molecules," he says. "Using mechanical methods of administration can potentially enable more drugs to have enhanced absorption."

While the capsule used in this study released its payload in the small intestine, it could also be used to target the stomach or colon by changing the pH at which the gelatin coating dissolves. The researchers also plan to explore the possibility of delivering other protein drugs such as GLP1 receptor agonist, which is sometimes used to treat type 2 diabetes. The capsules could also be used to deliver topical drugs to treat ulcerative colitis and other inflammatory conditions by maximizing the local concentration of the drugs in the tissue to help treat the inflammation.

Read more at Science Daily

Robotic lightning bugs take flight

Fireflies that light up dusky backyards on warm summer evenings use their luminescence for communication -- to attract a mate, ward off predators, or lure prey.

These glimmering bugs also sparked the inspiration of scientists at MIT. Taking a cue from nature, they built electroluminescent soft artificial muscles for flying, insect-scale robots. The tiny artificial muscles that control the robots' wings emit colored light during flight.

This electroluminescence could enable the robots to communicate with each other. If sent on a search-and-rescue mission into a collapsed building, for instance, a robot that finds survivors could use lights to signal others and call for help.

The ability to emit light also brings these microscale robots, which weigh barely more than a paper clip, one step closer to flying on their own outside the lab. These robots are so lightweight that they can't carry sensors, so researchers must track them using bulky infrared cameras that don't work well outdoors. Now, they've shown that they can track the robots precisely using the light they emit and just three smartphone cameras.

"If you think of large-scale robots, they can communicate using a lot of different tools -- Bluetooth, wireless, all those sorts of things. But for a tiny, power-constrained robot, we are forced to think about new modes of communication. This is a major step toward flying these robots in outdoor environments where we don't have a well-tuned, state-of-the-art motion tracking system," says Kevin Chen, who is the D. Reid Weedon, Jr. Assistant Professor in the Department of Electrical Engineering and Computer Science (EECS), the head of the Soft and Micro Robotics Laboratory in the Research Laboratory of Electronics (RLE), and the senior author of the paper.

He and his collaborators accomplished this by embedding miniscule electroluminescent particles into the artificial muscles. The process adds just 2.5 percent more weight without impacting the flight performance of the robot.

Joining Chen on the paper are EECS graduate students Suhan Kim, the lead author, and Yi-Hsuan Hsiao; Yu Fan Chen SM '14, PhD '17; and Jie Mao, an associate professor at Ningxia University. The research was published this month in IEEE Robotics and Automation Letters.

A light-up actuator

These researchers previously demonstrated a new fabrication technique to build soft actuators, or artificial muscles, that flap the wings of the robot. These durable actuators are made by alternating ultrathin layers of elastomer and carbon nanotube electrode in a stack and then rolling it into a squishy cylinder. When a voltage is applied to that cylinder, the electrodes squeeze the elastomer, and the mechanical strain flaps the wing.

To fabricate a glowing actuator, the team incorporated electroluminescent zinc sulphate particles into the elastomer but had to overcome several challenges along the way.

First, the researchers had to create an electrode that would not block light. They built it using highly transparent carbon nanotubes, which are only a few nanometers thick and enable light to pass through.

However, the zinc particles only light up in the presence of a very strong and high-frequency electric field. This electric field excites the electrons in the zinc particles, which then emit subatomic particles of light known as photons. The researchers use high voltage to create a strong electric field in the soft actuator, and then drive the robot at a high frequency, which enables the particles to light up brightly.

"Traditionally, electroluminescent materials are very energetically costly, but in a sense, we get that electroluminescence for free because we just use the electric field at the frequency we need for flying. We don't need new actuation, new wires, or anything. It only takes about 3 percent more energy to shine out light," Kevin Chen says.

As they prototyped the actuator, they found that adding zinc particles reduced its quality, causing it to break down more easily. To get around this, Kim mixed zinc particles into the top elastomer layer only. He made that layer a few micrometers thicker to accommodate for any reduction in output power.

While this made the actuator 2.5 percent heavier, it emitted light without impacting flight performance.

"We put a lot of care into maintaining the quality of the elastomer layers between the electrodes. Adding these particles was almost like adding dust to our elastomer layer. It took many different approaches and a lot of testing, but we came up with a way to ensure the quality of the actuator," Kim says.

Adjusting the chemical combination of the zinc particles changes the light color. The researchers made green, orange, and blue particles for the actuators they built; each actuator shines one solid color.

They also tweaked the fabrication process so the actuators could emit multicolored and patterned light. The researchers placed a tiny mask over the top layer, added zinc particles, then cured the actuator. They repeated this process three times with different masks and colored particles to create a light pattern that spelled M-I-T.

Following the fireflies

Once they had finetuned the fabrication process, they tested the mechanical properties of the actuators and used a luminescence meter to measure the intensity of the light.

From there, they ran flight tests using a specially designed motion-tracking system. Each electroluminescent actuator served as an active marker that could be tracked using iPhone cameras. The cameras detect each light color, and a computer program they developed tracks the position and attitude of the robots to within 2 millimeters of state-of-the-art infrared motion capture systems.

"We are very proud of how good the tracking result is, compared to the state-of-the-art. We were using cheap hardware, compared to the tens of thousands of dollars these large motion-tracking systems cost, and the tracking results were very close," Kevin Chen says.

Read more at Science Daily

'Ears' for rover Perseverance's exploration of Mars

For two decades, Roger Wiens has built instruments to give humans eyes and a nose on Mars -- and now he's helping add ears as well.

Wiens, a professor of Earth, Atmospheric, and Planetary Sciences in the College of Science at Purdue University, and an expert in Mars robotics technology, led the team that built SuperCam, a device on the Perseverance Mars rover that includes a laser for zapping rocks as well as the microphone that brought the first recordings of Mars to Earth.

"When I was at Los Alamos National Laboratory, I started looking around to see if there were any Department of Energy technologies that we might be able to harness and use for planetary science, and that's where Curiosity's ChemCam, which later evolved into Perseverance's SuperCam, came from," Wiens said.

SuperCam incorporates a technology that uses a pulsed laser beam to pulverize tiny bits of rock samples up to 30 feet away. The instrument collects the light from the brief flash emitted in the process, allowing scientists to analyze rocks that its arm can't reach and to "see" and analyze samples even through Mars dust that coats the rocks.

In incorporating the microphone into SuperCam, Wiens and his collaborators have opened up opportunities for a range of science and research on the Martian surface that was never possible before, including helping analyze rock and recording sounds.

"When we zap these rocks, we can find out more about their hardness and composition by listening to the change in sound as a number of laser shots get fired into the rock in the same spots," Wiens said. "We can hear the helicopter Ingenuity, which is something we didn't expect to be able to hear. We can hear the wind and measure the speed and direction, as well as measure the size and speed of dust devils. We can listen to the rover's own sounds and monitor health and safety the same way you gauge your car's well-being by listening to the motor. Things sound different on Earth because the rover's ears are shaped different from ours and the atmosphere is so different, but we're making recordings and learning things every other day."

Read more at Science Daily

Scientists develop insect-sized flying robots with flapping wings

A new drive system for flapping wing autonomous robots has been developed by a University of Bristol team, using a new method of electromechanical zipping that does away with the need for conventional motors and gears.

This new advance, published today in the journal Science Robotics, could pave the way for smaller, lighter and more effective micro flying robots for environmental monitoring, search and rescue, and deployment in hazardous environments.

Until now, typical micro flying robots have used motors, gears and other complex transmission systems to achieve the up-and-down motion of the wings. This has added complexity, weight and undesired dynamic effects.

Taking inspiration from bees and other flying insects, researchers from Bristol's Faculty of Engineering, led by Professor of Robotics Jonathan Rossiter, have successfully demonstrated a direct-drive artificial muscle system, called the Liquid-amplified Zipping Actuator (LAZA), that achieves wing motion using no rotating parts or gears.

The LAZA system greatly simplifies the flapping mechanism, enabling future miniaturization of flapping robots down to the size of insects.

In the paper, the team show how a pair of LAZA-powered flapping wings can provide more power compared with insect muscle of the same weight, enough to fly a robot across a room at 18 body lengths per second.

They also demonstrated how the LAZA can deliver consistent flapping over more than one million cycles, important for making flapping robots that can undertake long-haul flights.

The team expect the LAZA to be adopted as a fundamental building block for a range of autonomous insect-like flying robots.

Dr Tim Helps, lead author and developer of the LAZA system said "With the LAZA, we apply electrostatic forces directly on the wing, rather than through a complex, inefficient transmission system. This leads to better performance, simpler design, and will unlock a new class of low-cost, lightweight flapping micro-air vehicles for future applications, like autonomous inspection of off-shore wind turbines."

Read more at Science Daily

New law of physics helps humans and robots grasp the friction of touch

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.

Read more at Science Daily

Emerging robotics technology may lead to better buildings in less time

 Emerging robotics technology may soon help construction companies and contractors create buildings in less time at higher quality and at lower costs.

Purdue University innovators developed and are testing a novel construction robotic system that uses an innovative mechanical design with advances in computer vision sensing technology to work in a construction setting.

The technology was developed with support from the National Science Foundation.

"Our work helps to address workforce shortages in the construction industry by automating key construction operations," said Jiansong Zhang, an assistant professor of construction management technology in the Purdue Polytechnic Institute. "On a construction site, there are many unknown factors that a construction robot must be able to account for effectively. This requires much more advanced sensing and reasoning technologies than those commonly used in a manufacturing environment."

The Purdue team's custom end effector design allows for material to be both placed and fastened in the same operation using the same arm, limiting the amount of equipment that is required to complete a given task.

Computer vision algorithms developed for the project allow the robotic system to sense building elements and match them to building information modeling (BIM) data in a variety of environments, and keep track of obstacles or safety hazards in the system's operational context.

"By basing the sensing for our robotic arm around computer vision technology, rather than more limited-scope and expensive sensing systems, we have the capability to complete many sensing tasks with a single affordable sensor," Zhang said. "This allows us to implement a more robust and versatile system at a lower cost."

Undergraduate researchers in Zhang's Automation and Intelligent Construction (AutoIC) Lab helped create this robotic technology.

The innovators worked with the Purdue Research Foundation Office of Technology Commercialization to patent the technology.

This work will be featured at OTC's 2021 Technology Showcase: The State of Innovation. The annual showcase, being held virtually this year Feb. 10-11, will feature novel innovations from inventors at Purdue and across the state of Indiana.

From Science Daily

Inspired by cheetahs, researchers build fastest soft robots yet

Inspired by the biomechanics of cheetahs, researchers have developed a new type of soft robot that is capable of moving more quickly on solid surfaces or in the water than previous generations of soft robots. The new soft robotics are also capable of grabbing objects delicately -- or with sufficient strength to lift heavy objects.

"Cheetahs are the fastest creatures on land, and they derive their speed and power from the flexing of their spines," says Jie Yin, an assistant professor of mechanical and aerospace engineering at North Carolina State University and corresponding author of a paper on the new soft robots.

"We were inspired by the cheetah to create a type of soft robot that has a spring-powered, 'bistable' spine, meaning that the robot has two stable states," Yin says. "We can switch between these stable states rapidly by pumping air into channels that line the soft, silicone robot. Switching between the two states releases a significant amount of energy, allowing the robot to quickly exert force against the ground. This enables the robot to gallop across the surface, meaning that its feet leave the ground.

"Previous soft robots were crawlers, remaining in contact with the ground at all times. This limits their speed."

The fastest soft robots until now could move at speeds of up to 0.8 body lengths per second on flat, solid surfaces. The new class of soft robots, which are called "Leveraging Elastic instabilities for Amplified Performance" (LEAP), are able to reach speeds of up to 2.7 body lengths per second -- more than three times faster -- at a low actuation frequency of about 3Hz. These new robots are also capable of running up steep inclines, which can be challenging or impossible for soft robots that exert less force against the ground.

These "galloping" LEAP robots are approximately 7 centimeters long and weigh about 45 grams.

The researchers also demonstrated that the LEAP design could improve swimming speeds for soft robots. Attaching a fin, rather than feet, a LEAP robot was able to swim at a speed of 0.78 body lengths per second, as compared to 0.7 body lengths per second for the previous fastest swimming soft robot.

"We also demonstrated the use of several soft robots working together, like pincers, to grab objects," Yin says. "By tuning the force exerted by the robots, we were able to lift objects as delicate as an egg, as well as objects weighing 10 kilograms or more."

The researchers note that this work serves as a proof of concept, and are optimistic that they can modify the design to make LEAP robots that are even faster and more powerful.

"Potential applications include search and rescue technologies, where speed is essential, and industrial manufacturing robotics," Yin says. "For example, imagine production line robotics that are faster, but still capable of handling fragile objects.

Read more at Science Daily

A smart artificial hand for amputees merges user and robotic control

EPFL scientists are developing new approaches for improved control of robotic hands -- in particular for amputees -- that combines individual finger control and automation for improved grasping and manipulation. This interdisciplinary proof-of-concept between neuroengineering and robotics was successfully tested on three amputees and seven healthy subjects. The results are published in today's issue of Nature Machine Intelligence.

The technology merges two concepts from two different fields. Implementing them both together had never been done before for robotic hand control, and contributes to the emerging field of shared control in neuroprosthetics.

One concept, from neuroengineering, involves deciphering intended finger movement from muscular activity on the amputee's stump for individual finger control of the prosthetic hand which has never before been done. The other, from robotics, allows the robotic hand to help take hold of objects and maintain contact with them for robust grasping.

"When you hold an object in your hand, and it starts to slip, you only have a couple of milliseconds to react," explains Aude Billard who leads EPFL's Learning Algorithms and Systems Laboratory. "The robotic hand has the ability to react within 400 milliseconds. Equipped with pressure sensors all along the fingers, it can react and stabilize the object before the brain can actually perceive that the object is slipping. "

How shared control works

The algorithm first learns how to decode user intention and translates this into finger movement of the prosthetic hand. The amputee must perform a series of hand movements in order to train the algorithm that uses machine learning. Sensors placed on the amputee's stump detect muscular activity, and the algorithm learns which hand movements correspond to which patterns of muscular activity. Once the user's intended finger movements are understood, this information can be used to control individual fingers of the prosthetic hand.

"Because muscle signals can be noisy, we need a machine learning algorithm that extracts meaningful activity from those muscles and interprets them into movements," says Katie Zhuang first author of the publication.

Next, the scientists engineered the algorithm so that robotic automation kicks in when the user tries to grasp an object. The algorithm tells the prosthetic hand to close its fingers when an object is in contact with sensors on the surface of the prosthetic hand. This automatic grasping is an adaptation from a previous study for robotic arms designed to deduce the shape of objects and grasp them based on tactile information alone, without the help of visual signals.

Many challenges remain to engineer the algorithm before it can be implemented in a commercially available prosthetic hand for amputees. For now, the algorithm is still being tested on a robot provided by an external party.

Read more at Science Daily

3D-printed robot hand plays the piano

Robot hand playing the piano.

Scientists have developed a 3D-printed robotic hand which can play simple musical phrases on the piano by just moving its wrist. And while the robot is no virtuoso, it demonstrates just how challenging it is to replicate all the abilities of a human hand, and how much complex movement can still be achieved through design.

The robot hand, developed by researchers at the University of Cambridge, was made by 3D-printing soft and rigid materials together to replicate of all the bones and ligaments -- but not the muscles or tendons -- in a human hand. Even though this limited the robot hand's range of motion compared to a human hand, the researchers found that a surprisingly wide range of movement was still possible by relying on the hand's mechanical design.

Using this 'passive' movement -- in which the fingers cannot move independently -- the robot was able to mimic different styles of piano playing without changing the material or mechanical properties of the hand. The results, reported in the journal Science Robotics, could help inform the design of robots that are capable of more natural movement with minimal energy use.

Complex movement in animals and machines results from the interplay between the brain (or controller), the environment and the mechanical body. The mechanical properties and design of systems are important for intelligent functioning, and help both animals and machines to move in complex ways without expending unnecessary amounts of energy.

"We can use passivity to achieve a wide range of movement in robots: walking, swimming or flying, for example," said Josie Hughes from Cambridge's Department of Engineering, the paper's first author. "Smart mechanical design enables us to achieve the maximum range of movement with minimal control costs: we wanted to see just how much movement we could get with mechanics alone."

Over the past several years, soft components have begun to be integrated into robotics design thanks to advances in 3D printing techniques, which has allowed researchers to add complexity to these passive systems.

The human hand is incredibly complex, and recreating all of its dexterity and adaptability in a robot is a massive research challenge. Most of today's advanced robots are not capable of manipulation tasks which small children can perform with ease.

"The basic motivation of this project is to understand embodied intelligence, that is, the intelligence in our mechanical body," said Dr Fumiya Iida, who led the research. "Our bodies consist of smart mechanical designs such as bones, ligaments, and skins that help us behave intelligently even without active brain-led control. By using the state-of-the-art 3D printing technology to print human-like soft hands, we are now able to explore the importance of physical designs, in isolation from active control, which is impossible to do with human piano players as the brain cannot be 'switched off' like our robot."

"Piano playing is an ideal test for these passive systems, as it's a complex and nuanced challenge requiring a significant range of behaviours in order to achieve different playing styles," said Hughes.

The robot was 'taught' to play by considering how the mechanics, material properties, environment and wrist actuation all affect the dynamic model of the hand. By actuating the wrist, it is possible to choose how the hand interacts with the piano, allowing the embodied intelligence of the hand to determine how it interacts with the environment.

The researchers programmed the robot to play a number of short musical phrases with clipped (staccato) or smooth (legato) notes, achieved through the movement of the wrist. "It's just the basics at this point, but even with this single movement, we can still get quite complex and nuanced behaviour," said Hughes.

Despite the limitations of the robot hand, the researchers say their approach will drive further research into the underlying principles of skeletal dynamics to achieve complex movement tasks, as well as learning where the limitations for passive movement systems lie.

"This approach to mechanical design can change how we build robotics," said Iida. "The fabrication approach allows us to design mechanically intelligent structures in a way that is highly scalable."

Read more at Science Daily

Artificial muscles power up with new gel-based robotics

(a) Overview of wearing set-up of the assist wear. (b) Structure of the multilayered PVC gel actuator with two types of anode mesh electrodes. The red layer with small holes is comprised of slide electrodes to minimize the friction with the slide shafts. (c) Contraction and expansion movement of the stretching type actuator with the DC field turned on and off. (d) FlexiForce sensor-based motion detection (position estimator). (e) Power and controller.

Scientists are one step closer to artificial muscles. Orthotics have come a long way since their initial wood and strap designs, yet innovation lapsed when it came to compensating for muscle power -- until now.

A collaborative research team has designed a wearable robot to support a person's hip joint while walking. The team, led by Minoru Hashimoto, a professor of textile science and technology at Shinshu University in Japan, published the details of their prototype in Smart Materials and Structures, a journal published by the Institute of Physics.

"With a rapidly aging society, an increasing number of elderly people require care after suffering from stroke, and other-age related disabilities. Various technologies, devices, and robots are emerging to aid caretakers," wrote Hashimoto, noting that several technologies meant to assist a person with walking are often cumbersome to the user. "[In our] current study, [we] sought to develop a lightweight, soft, wearable assist wear for supporting activities of daily life for older people with weakened muscles and those with mobility issues."

The wearable system consists of plasticized polyvinyl chloride (PVC) gel, mesh electrodes, and applied voltage. The mesh electrodes sandwich the gel, and when voltage is applied, the gel flexes and contracts, like a muscle. It's a wearable actuator, the mechanism that causes movement.

"We thought that the electrical mechanical properties of the PVC gel could be used for robotic artificial muscles, so we started researching the PVC gel," said Hashimoto. "The ability to add voltage to PVC gel is especially attractive for high speed movement, and the gel moves with high speed with just a few hundred volts."

In a preliminary evaluation, a stroke patient with some paralysis on one side of his body walked with and without the wearable system.

"We found that the assist wear enabled natural movement, increasing step length and decreasing muscular activity during straight line walking," wrote Hashimoto. The researchers also found that adjusting the charge could change the level of assistance the actuator provides.

The robotic system earned first place in demonstrations with their multilayer PVC gel artificial muscle at the, "24th International Symposium on Smart Structures and Materials & Nondestructive Evaluation and Health Monitoring" for SPIE the international society for optics and photonics.

Read more at Science Daily