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In San Francisco, California, the self-driving tech company – owned by Google parent Alphabet – moved a step closer to launching a fully autonomous commercialized ride-hailing service, as is currently being operated by its chief rival, General Motors-owned Cruise. And in Phoenix, Arizona, Waymo’s driverless service has been made available to members of the general public in the central Downtown area. The breakthrough in San Francisco has come via the approval by the California Department of Motor Vehicles to an amendment of the company’s current permit to operate. Now Waymo will be able to charge fees for driverless services in its autonomous vehicles (AVs), such as deliveries. Once it has operated a driverless service on public roads in the city for a total of 30 days, it will then be eligible to submit an application to the California Public Utilities Commission (CPUC) for a permit that would enable it to charge fares for passenger-only autonomous rides in its vehicles. This is the same permit that provided the greenlight for Cruise’s commercial driverless ride-hail service at the start of June. The CPUC awarded a drivered deployment permit to Waymo in February which allowed the company to charge its ‘trusted testers’ for autonomous rides with a safety operator on board. The trusted tester program comprises vetted members of the public who have applied to use the service and have signed an NDA which means they will not talk about their experiences publicly. In downtown Phoenix, the extension of the driverless ride-hail service is the latest evidence of the incremental progress Waymo has made in the city. Over the past couple of years, the company has operated a paid rider-only service in some of Phoenix’s eastern suburbs, such as Gilbert, Mesa, Chandler and Tempe. Earlier this year it moved into the busier, more central downtown area, where driverless rides were made available for trusted testers. It also trialled an autonomous service for employees at Phoenix Sky Harbor International Airport, albeit with a safety operator on board. In early November, it was confirmed that airport rides would be offered to trusted testers, although again Waymo made clear that there would be a specialist in the driver’s seat, initially at least.
Scientists from the Max Planck Institute for Intelligent Systems and the Max Planck Institute for Solid State Research develop organic microparticles that can steer through biological fluids and dissolved blood in unprecedented ways. Even in very salty liquids, the microswimmers can be propelled forward at high speed by visible light, either individually or as a swarm. Additionally, they are partially biocompatible and can take up and release cargo on demand. The material properties are so ideal they could pave the way toward designing semi-autonomous microrobots applied in biomedicine. Science Fiction novelists couldn't have come up with a crazier plot: microrobots streaming through blood or through other fluids in our body which are driven by light, can carry drugs to cancer cells and drop off the medication on the spot. What sounds like a far-fetched fantasy, is however the short summary of a research project published in the journal Science Robotics. The microswimmers presented in the work bear the potential to one day perform tasks in living organisms or biological environments that are not easily accessible otherwise. Looking even further ahead, the swimmers could perhaps one day help treat cancer or other diseases. In their recent paper "Light-driven carbon nitride microswimmers with propulsion in biological and ionic media and responsive on-demand drug delivery," a team of scientists from the Max Planck Institute for Intelligent Systems (MPI-IS) and its neighboring institute, the Max Planck Institute for Solid State Research (MPI-FKF), demonstrate organic microparticles that can steer through biological fluids and dissolved blood in an unprecedented way. Even in very salty liquids, the microswimmers can be propelled forward at high speed by visible light, either individually or as a swarm. Additionally, they are partially biocompatible and can take up and release cargo on demand. At MPI-IS, scientists from the Physical Intelligence Department led by Metin Sitti were involved and at MPI-FKF, scientists from the Nanochemistry Department led by Bettina Lotsch. Designing and fabricating such highly advanced microswimmers seemed impossible up until now. Locomotion by light energy is hindered by the salts found in water or the body. This requires a sophisticated design that is difficult to scale up. Additionally, controlling the robots from the outside is challenging and often costly. Controlled cargo uptake and on-the-spot delivery is another supreme discipline in the field of nanorobotics. The scientists used a porous two-dimensional carbon nitride (CNx) that can be synthesized from organic materials, for instance, urea. Like the solar cells of a photovoltaic panel, carbon nitride can absorb light which then provides the energy to propel the robot forward when light illuminates the particle surface. High ion tolerance "The use of light as the energy source of propulsion is very convenient when doing experiments in a petri dish or for applications directly under the skin," says Filip Podjaski, a group leader in the Nanochemistry Department at MPI-FKF. "There is just one problem: even tiny concentrations of salts prohibit light-controlled motion. Salts are found in all biological liquids: in blood, cellular fluids, digestive fluids etc. However, we have shown that our CNx microswimmers function in all biological liquids -- even when the concentration of salt ions is very high. This is only possible due to a favorable interplay of different factors: efficient light energy conversion as the driving force, as well as the porous structure of the nanoparticles, which allows ions to flow through them, reducing the resistance created by salt, so to speak. In addition, in this material, light favors the mobility of ions -- making the particle even faster."
Columbia Engineering researchers use AI to teach robots to make appropriate reactive human facial expressions, an ability that could build trust between humans and their robotic co-workers and care-givers. While our facial expressions play a huge role in building trust, most robots still sport the blank and static visage of a professional poker player. With the increasing use of robots in locations where robots and humans need to work closely together, from nursing homes to warehouses and factories, the need for a more responsive, facially realistic robot is growing more urgent. Long interested in the interactions between robots and humans, researchers in the Creative Machines Lab at Columbia Engineering have been working for five years to create EVA, a new autonomous robot with a soft and expressive face that responds to match the expressions of nearby humans. The research will be presented at the ICRA conference on May 30, 2021, and the robot blueprints are open-sourced on Hardware-X (April 2021). "The idea for EVA took shape a few years ago, when my students and I began to notice that the robots in our lab were staring back at us through plastic, googly eyes," said Hod Lipson, James and Sally Scapa Professor of Innovation (Mechanical Engineering) and director of the Creative Machines Lab. Lipson observed a similar trend in the grocery store, where he encountered restocking robots wearing name badges, and in one case, decked out in a cozy, hand-knit cap. "People seemed to be humanizing their robotic colleagues by giving them eyes, an identity, or a name," he said. "This made us wonder, if eyes and clothing work, why not make a robot that has a super-expressive and responsive human face?" While this sounds simple, creating a convincing robotic face has been a formidable challenge for roboticists. For decades, robotic body parts have been made of metal or hard plastic, materials that were too stiff to flow and move the way human tissue does. Robotic hardware has been similarly crude and difficult to work with -- circuits, sensors, and motors are heavy, power-intensive, and bulky. The first phase of the project began in Lipson's lab several years ago when undergraduate student Zanwar Faraj led a team of students in building the robot's physical "machinery." They constructed EVA as a disembodied bust that bears a strong resemblance to the silent but facially animated performers of the Blue Man Group. EVA can express the six basic emotions of anger, disgust, fear, joy, sadness, and surprise, as well as an array of more nuanced emotions, by using artificial "muscles" (i.e. cables and motors) that pull on specific points on EVA's face, mimicking the movements of the more than 42 tiny muscles attached at various points to the skin and bones of human faces. "The greatest challenge in creating EVA was designing a system that was compact enough to fit inside the confines of a human skull while still being functional enough to produce a wide range of facial expressions," Faraj noted.
NASA's Ingenuity helicopter just completed a much more ambitious third flight. As Space.com reports, the Mars aircraft ventured about 164 feet north of its home base (slightly more than half the length of a football field) at a speed of about 4.5MPH. That may not sound like much, but Ingenuity only traveled 13 feet at 1.1MPH during its second flight — this was far enough that you almost have to squint to see Ingenuity in the photo above. There are only two potential flights left before NASA winds down its efforts in early May and shifts focus to the Perserverance rover's main mission. Expect these to be exciting, though. Project manager Mimi Aung said the final two journeys should be "really adventurous" and test the limits of the flying machine. The successes so far are already likely to have a significant impact on future Mars exploration. Ingenuity is proof that aircraft can fly on the planet despite its very low atmospheric density, and there's now a good chance that later missions will use drones to survey Mars from perspectives that simply weren't available before.
In ten years artificially intelligent robots will be living and working with us, according to Dr. Mark Sagar, CEO of Soul Machines, an Auckland, New Zealand-based company that develops intelligent, emotionally responsive avatars. Sagar, an AI engineer, is the inventor of a virtual nervous system that powers autonomous animated avatars like Baby X — a virtual infant that learns through experience and can “feel” emotions. “We are creating realistic adult avatars serving as virtual assistants. You can use them to plug into existing systems like IBM Watson or Cortana — putting a face on a chatbot,” said Sagar. Within a decade humans will be interacting with lifelike emotionally-responsive AI robots, very similar to the premise of the the HBO hit series Westworld, said Sagar. But before that scenario becomes a reality robotics will have to catch up to AI technology. “Robotics technology is not really at the level of control that’s required,” he said.
Most technologies are made from steel, concrete, chemicals, and plastics, which degrade over time and can produce harmful ecological and health side effects. It would thus be useful to build technologies using self-renewing and biocompatible materials, of which the ideal candidates are living systems themselves. Thus, scientists have developed a method that designs completely biological machines from the ground up: computers automatically design new machines in simulation, and the best designs are then built by combining together different biological tissues. People may use this approach to design a variety of living machines to safely deliver drugs inside the human body, help with environmental remediation, or further broaden our understanding of the diverse forms and functions life may adopt.
Cornell engineers have created a synthetic vascular system for soft robots capable of pumping an energy-dense hydraulic liquid that stores and deploys energy in an integrated design. Untethered robots suffer from a stamina problem. A possible solution: a circulating liquid – “robot blood” – to store energy and power its applications for sophisticated, long-duration tasks. Humans and other complex organisms manage life through integrated systems. Humans store energy in fat reserves spread across the body, and an intricate circulatory system transports oxygen and nutrients to power trillions of cells. But crack open the hood of an untethered robot and things are much more segmented: Over here is the solid battery and over there are the motors, with cooling systems and other components scattered throughout. Cornell researchers have recently created a synthetic vascular system capable of pumping an energy-dense hydraulic liquid that stores energy, transmits force, operates appendages and provides structure, all in an integrated design. “In nature we see how long organisms can operate while doing sophisticated tasks. Robots can’t perform similar feats for very long,” said Rob Shepherd, associate professor of mechanical and aerospace engineering. “Our bio-inspired approach can dramatically increase the system’s energy density while allowing soft robots to remain mobile for far longer.” Shepherd, director of the Organic Robotics Lab, is senior author of “Electrolytic Vascular Systems for Energy Dense Robots,” which published June 19 in Nature. Doctoral student Cameron Aubin is lead author.
Researchers are trialling the use of drones to monitor coffee plant health in Thailand in a bid to prevent the spread of disease. Around 95 million cups of coffee are drunk a day in the UK alone, but the coffee plant is susceptible to a fungal disease known as coffee rust. This disease is devastating to the plant and can wipe out vast swathes of crops or even entire plantations. If a coffee plantation is hit by disease it can destroy an entire family's livelihood. In the lower-income regions where coffee is grown, farmers also tend not to use expensive fungicides that could prevent the disease. This is also because they want to grow coffee without using chemicals to secure organic certification. Now, a team led by Dr. Oliver Windram from the Department of Life Sciences at Imperial are hoping to be able to prevent the spread of coffee rust using drones, and have been testing this out in the coffee growing areas of Thailand. The idea is that if farmers can spot that disease has started to affect their crops, they can remove the affected plants to prevent it spreading further. This method would also allow them to control disease without chemical fungicides.
MIT Media Lab researchers have developed a machine-learning model that takes computers a step closer to interpreting our emotions as naturally as humans do. In the growing field of “affective computing,” robots and computers are being developed to analyze facial expressions, interpret our emotions, and respond accordingly. Applications include, for instance, monitoring an individual’s health and well-being, gauging student interest in classrooms, helping diagnose signs of certain diseases, and developing helpful robot companions. A challenge, however, is people express emotions quite differently, depending on many factors. General differences can be seen among cultures, genders, and age groups. But other differences are even more fine-grained: The time of day, how much you slept, or even your level of familiarity with a conversation partner leads to subtle variations in the way you express, say, happiness or sadness in a given moment. Human brains instinctively catch these deviations, but machines struggle. Deep-learning techniques were developed in recent years to help catch the subtleties, but they’re still not as accurate or as adaptable across different populations as they could be. The Media Lab researchers have developed a machine-learning model that outperforms traditional systems in capturing these small facial expression variations, to better gauge mood while training on thousands of images of faces. Moreover, by using a little extra training data, the model can be adapted to an entirely new group of people, with the same efficacy. The aim is to improve existing affective-computing technologies. “This is an unobtrusive way to monitor our moods,” says Oggi Rudovic, a Media Lab researcher and co-author on a paper describing the model, which was presented last week at the Conference on Machine Learning and Data Mining. “If you want robots with social intelligence, you have to make them intelligently and naturally respond to our moods and emotions, more like humans.” Co-authors on the paper are: first author Michael Feffer, an undergraduate student in electrical engineering and computer science; and Rosalind Picard, a professor of media arts and sciences and founding director of the Affective Computing research group.
We often think of robots as superior to ourselves, but when it comes to the abilities afforded us by our muscles, robots have a hard time keeping up. Researchers at the University of Colorado Boulder are working to change that with newly-developed soft muscles that work a lot like our own, and can even heal themselves from certain kinds of damage. The new robo-muscles are called hydraulically amplified self-healing electrostatic actuators, or HASEL for short. They’re a potential replacement for hard metal motors and hydraulic pistons that robotics designers often lean on to provide their creations with movement. In a pair of papers published this week in Science and Science Robotics, the researchers describe their biologically-inspired soft robot muscles as having the potential to revolutionize how robots move. The muscles are built using small flexible pouches which are filled with oil. The pouches have electrodes embedded in them and when electricity is applied the oil tenses up and creates an artificial muscle contraction. When the electricity is cut off, it relaxes again, and the faux muscles can flex and relax instantly, just like a real muscle. “HASEL actuators synergize the strengths of soft fluidic and soft electrostatic actuators, and thus combine versatility and performance like no other artificial muscle before,” Christoph Keplinger, senior author of the research, explains. “Just like biological muscle, HASEL actuators can reproduce the adaptability of an octopus arm, the speed of a hummingbird and the strength of an elephant.” What’s particularly interesting about this new robotic muscle tech is that it’s incredibly cheap to produce. The oil, elastic bags, and electrodes that make up the muscle only cost pennies, and they work as well or better than a traditional electric motor. However, the one drawback is that the electricity the muscles crave can be a steep requirement, and a bot equipped with such muscles might burn through its power reserves at a rapid pace. Still, it’s a remarkable breakthrough in the field of soft robotics and if further work on the concept can yield strong muscles without such a high power demand, it could change the way the robots of the future are designed and built.
A glacier crevasse has to be one of the worst places you could ever decide to fly a drone. It’s deep, dark, narrow, windy, and full of all kinds of nasty pointy bits, any one of which could collapse onto you at any time. This is also why you’d never want to enter one yourself, and why there aren’t any robots that are really able to go down into them to explore: it’s just horribly dangerous. From time to time, though, humans fall into crevasses, and then other humans have to (first) find them and then (hopefully) rescue them. Switzerland-based startup Flyability partnered with the mountain rescue team at Zermatt Glacier in the Swiss Alps to offer them the services of Gimball, which is quite possibly the only robot that doesn’t care even a little bit whether you drop it into the bowels of a glacier. The drone took its HD camera and powerful lighting system deep into the ice, and came back out alive with video to prove it. There are a bunch of other drones that come with protective cages of one sort or another, but Gimball is unique in that its protective cage is rotationally decoupled from the drone itself. This means that when the cage runs into something (like a massive ice wall), the force of the impact is absorbed by the cage and translated into rotational energy, while the drone inside remains stable and continues traveling generally in the direction that it was traveling in before. The upshot is that running into walls (or the floor or ceiling or whatever) is just not a big deal, and even untrained pilots can fly Gimball in treacherous places and still get back out in one piece.
For the past several years, researchers at the University of Illinois at Urbana-Champaign have reverse-engineered native biological tissues and organs — creating tiny walking “bio-bots” powered by muscle cells and controlled with electrical and optical pulses. Now, in an open-access cover paper in Nature Protocols, the researchers are sharing a protocol with engineering details for their current generation of millimeter-scale soft robotic bio-bots*. Using 3D-printed skeletons, these devices would be coupled to tissue-engineered skeletal muscle actuators to drive locomotion across 2D surfaces, and could one day be used for studies of muscle development and disease, high-throughput drug testing, and dynamic implants, among other applications.
On Oct. 26, 2016, a pair of Hornets flying above an empty part of California opened their bellies and released a robotic swarm. With machine precision, the fast-moving unmanned flying machines took flight, then moved to a series of waypoints, meeting objectives set for the swarm by a human controller. The brief flight of 103 tiny drones heralds a new age in how, exactly, America uses robots at war. The Pentagon’s worked with Perdix drones since 2013, with the October flight using the military’s 6th generation of the devices. F/A-18 Hornets, long-serving Navy fighters, carried the drones and released them from flare dispensers. The small drones were the subject of an episode of CBS’s 60 Minutes, and they move so fast they’re hard to film. Below, in a clip from the Department of Defense, the drones are barely visible as dark blurs beneath the fighters. Captured by telemetry video on the ground, the swarm is clearly visible. First it appears as if from nowhere, moves as one towards a new set of objectives. This drone swarm was a product of the Strategic Capabilities Office, and outgoing Secretary of Defense Ash Carter praised the work, saying “This is the kind of cutting-edge innovation that will keep us a step ahead of our adversaries. This demonstration will advance our development of autonomous systems.” Autonomy and swarming are centerpieces in many predictions about the next century of war. The Predator, Reaper, and Global Hawk drones that have so far most embodied how the United States fights wars are big, expensive, and vulnerable machines, with human pilots and sensor operators controlling them remotely. These drones also operate in skies relatively free of threats, without fear that a hostile jet will shoot them down. That’s an approach that’s fine for counterinsurgency battles, an admittedly large part of the wars the Pentagon actually fights, but against a near-peer nation or any foe with sophisticated anti-air or electronic jamming equipment, Reapers are extremely vulnerable targets. Swarms, where several small flying robots work together to do the same job previously done by a larger craft are one way around that. A few $45,000 anti-air missiles are a cost-effective way to shoot down an $18 million Reaper, but firing that same anti-air missile at a smaller, commercial drone isn’t as effective, especially when there are still 102 other drones flying the same mission at the same time. Controlling that swarm is where autonomy comes in. With every Predator drone, there’s an actual joystick and flight controls for a human pilot, whose job it is to direct the uncrewed plane and maneuver it. That one-to-one ratio would be impossible to maintain with a small drone swarm, and given that the perdix drone has a listed flight time of “over 20 minutes,” it would be a lot of effort for a very short excursion.
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Image sensors measure light intensity, but angle, spectrum, and other aspects of light must also be extracted to significantly advance machine vision. In Applied Physics Letters, published by AIP Publishing, researchers at the University of Wisconsin-Madison, Washington University in St. Louis, and OmniVision Technologies highlight the latest nano-structured components integrated on image sensor chips that are most likely to make the biggest impact in multimodal imaging. The developments could enable autonomous vehicles to see around corners instead of just a straight line, biomedical imaging to detect abnormalities at different tissue depths, and telescopes to see through interstellar dust. “Image sensors will gradually undergo a transition to become the ideal artificial eyes of machines,” co-author Yurui Qu, from the University of Wisconsin-Madison, said. “An evolution leveraging the remarkable achievement of existing imaging sensors is likely to generate more immediate impacts.” Image sensors, which converts light into electrical signals, are composed of millions of pixels on a single chip. The challenge is how to combine and miniaturize multifunctional components as part of the sensor. In their own work, the researchers detailed a promising approach to detect multiple-band spectra by fabricating an on-chip spectrometer. They deposited photonic crystal filters made up of silicon directly on top of the pixels to create complex interactions between incident light and the sensor. The pixels beneath the films record the distribution of light energy, from which light spectral information can be inferred. The device – less than a hundredth of a square inch in size – is programmable to meet various dynamic ranges, resolution levels, and almost any spectral regime from visible to infrared. The researchers built a component that detects angular information to measure depth and construct 3D shapes at subcellular scales. Their work was inspired by directional hearing sensors found in animals, like geckos, whose heads are too small to determine where sound is coming from in the same way humans and other animals can. Instead, they use coupled eardrums to measure the direction of sound within a size that is orders of magnitude smaller than the corresponding acoustic wavelength. Similarly, pairs of silicon nanowires were constructed as resonators to support optical resonance. The optical energy stored in two resonators is sensitive to the incident angle. The wire closest to the light sends the strongest current. By comparing the strongest and weakest currents from both wires, the angle of the incoming light waves can be determined. Millions of these nanowires can be placed on a 1-square-millimeter chip. The research could support advances in lensless cameras, augmented reality, and robotic vision.
Ultrasound measurements of muscle dynamics provide customized, activity-specific assistance People rarely walk at a constant speed and a single incline. We change speed when rushing to the next appointment, catching a crosswalk signal, or going for a casual stroll in the park. Slopes change all the time too, whether we're going for a hike or up a ramp into a building. In addition to environmental variably, how we walk is influenced by sex, height, age, and muscle strength, and sometimes by neural or muscular disorders such as stroke or Parkinson's Disease. This human and task variability is a major challenge in designing wearable robotics to assist or augment walking in real-world conditions. To date, customizing wearable robotic assistance to an individual's walking requires hours of manual or automatic tuning -- a tedious task for healthy individuals and often impossible for older adults or clinical patients. Now, researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a new approach in which robotic exosuit assistance can be calibrated to an individual and adapt to a variety of real-world walking tasks in a matter of seconds. The bioinspired system uses ultrasound measurements of muscle dynamics to develop a personalized and activity-specific assistance profile for users of the exosuit. "Our muscle-based approach enables relatively rapid generation of individualized assistance profiles that provide real benefit to the person walking," said Robert D. Howe, the Abbott and James Lawrence Professor of Engineering, and co-author of the paper. The research is published in Science Robotics. Previous bioinspired attempts at developing individualized assistance profiles for robotic exosuits focused on the dynamic movements of the limbs of the wearer. The SEAS researchers took a different approach. The research was a collaboration between Howe's Harvard Biorobotics Laboratory, which has extensive experience in ultrasound imaging and real-time image processing, and the Harvard Biodesign Lab, run by Conor J. Walsh, the Paul A. Maeder Professor of Engineering and Applied Sciences at SEAS, which develops soft wearable robots for augmenting and restoring human performance. "We used ultrasound to look under the skin and directly measured what the user's muscles were doing during several walking tasks," said Richard Nuckols, a Postdoctoral Research Associate at SEAS and co-first author of the paper. "Our muscles and tendons have compliance which means there is not necessarily a direct mapping between the movement of the limbs and that of the underlying muscles driving their motion."
Throughout human history, workers have thrived on ingenuity and invention, which has led us to maximise the utility of resources around us in pursuit of productivity and efficiency
Even today technology continues to evolve, and in recent times that innovation has delivered us intelligent technologies including AI, robotics, and automation. Once the stuff of science fiction, these new technologies are being adopted at an astounding rate, and data shows the pace of innovation is only going to continue in future.
Our recent forecast of the UK’s workforce for example, which looked at how automating technologies might impact jobs on a task by task basis, found that the equivalent of 1.4 million full-time roles could be automated by the end of this year. That’s the equivalent of 4.8% of work currently undertaken across the country.
Via Edumorfosis, juandoming
Artificial skin reacts to pain just like real skin, opening the way to better prosthetics, smarter robotics and less invasive options for skin grafts. Researchers have developed electronic artificial skin that reacts to pain just like real skin, opening the way to better prosthetics, smarter robotics and non-invasive alternatives to skin grafts. The prototype device developed by a team at RMIT University in Melbourne, Australia, can electronically replicate the way human skin senses pain. The device mimics the body's near-instant feedback response and can react to painful sensations with the same lighting speed that nerve signals travel to the brain. Lead researcher Professor Madhu Bhaskaran said the pain-sensing prototype was a significant advance towards next-generation biomedical technologies and intelligent robotics. "Skin is our body's largest sensory organ, with complex features designed to send rapid-fire warning signals when anything hurts," Bhaskaran said. "We're sensing things all the time through the skin but our pain response only kicks in at a certain point, like when we touch something too hot or too sharp. No electronic technologies have been able to realistically mimic that very human feeling of pain -- until now. Our artificial skin reacts instantly when pressure, heat or cold reach a painful threshold. It's a critical step forward in the future development of the sophisticated feedback systems that we need to deliver truly smart prosthetics and intelligent robotics." Functional sensing prototypes As well as the pain-sensing prototype, the research team has also developed devices using stretchable electronics that can sense and respond to changes in temperature and pressure. Bhaskaran, co-leader of the Functional Materials and Microsystems group at RMIT, said the three functional prototypes were designed to deliver key features of the skin's sensing capability in electronic form. With further development, the stretchable artificial skin could also be a future option for non-invasive skin grafts, where the traditional approach is not viable or not working. "We need further development to integrate this technology into biomedical applications but the fundamentals -- biocompatibility, skin-like stretchability -- are already there," Bhaskaran said.
A “mental model” developed at MIT aims to give robots human-like spatial perception. Wouldn't we all appreciate a little help around the house, especially if that help came in the form of a smart, adaptable, uncomplaining robot? Sure, there are the one-trick Roombas of the appliance world. But MIT engineers are envisioning robots more like home helpers, able to follow high-level, Siri-type commands, such as "Go to the kitchen and fetch me a coffee cup." To carry out such high-level tasks, researchers believe robots will have to be able to perceive their physical environment as humans do. "In order to make any decision in the world, you need to have a mental model of the environment around you," says Luca Carlone, assistant professor of aeronautics and astronautics at MIT. "This is something so effortless for humans. But for robots it's a painfully hard problem, where it's about transforming pixel values that they see through a camera, into an understanding of the world." Now Carlone and his students have developed a representation of spatial perception for robots that is modeled after the way humans perceive and navigate the world. The new model, which they call 3D Dynamic Scene Graphs, enables a robot to quickly generate a 3D map of its surroundings that also includes objects and their semantic labels (a chair versus a table, for instance), as well as people, rooms, walls, and other structures that the robot is likely seeing in its environment. The model also allows the robot to extract relevant information from the 3D map, to query the location of objects and rooms, or the movement of people in its path. "This compressed representation of the environment is useful because it allows our robot to quickly make decisions and plan its path," Carlone says. "This is not too far from what we do as humans. If you need to plan a path from your home to MIT, you don't plan every single position you need to take. You just think at the level of streets and landmarks, which helps you plan your route faster." Beyond domestic helpers, Carlone says robots that adopt this new kind of mental model of the environment may also be suited for other high-level jobs, such as working side by side with people on a factory floor or exploring a disaster site for survivors. He and his students, including lead author and MIT graduate student Antoni Rosinol, will present their findings this week at the Robotics: Science and Systems virtual conference. A mapping mix At the moment, robotic vision and navigation has advanced mainly along two routes: 3D mapping that enables robots to reconstruct their environment in three dimensions as they explore in real time; and semantic segmentation, which helps a robot classify features in its environment as semantic objects, such as a car versus a bicycle, which so far is mostly done on 2D images. Carlone and Rosinol's new model of spatial perception is the first to generate a 3D map of the environment in real-time, while also labeling objects, people (which are dynamic, contrary to objects), and structures within that 3D map. The key component of the team's new model is Kimera, an open-source library that the team previously developed to simultaneously construct a 3D geometric model of an environment, while encoding the likelihood that an object is, say, a chair versus a desk. "Like the mythical creature that is a mix of different animals, we wanted Kimera to be a mix of mapping and semantic understanding in 3D," Carlone says.
A team of researchers from Carnegie Mellon has made a breakthrough in the field of noninvasive robotic device control. Using a noninvasive brain-computer interface, they have developed the first-ever successful mind-controlled robotic arm exhibiting the ability to continuously track and follow a computer cursor. Being able to non-invasively control robotic devices using only thoughts will have broad applications, in particular benefiting the lives of paralyzed patients and those with movement disorders. BCIs have been shown to achieve good performance for controlling robotic devices using only the signals sensed from brain implants. When robotic devices can be controlled with high precision, they can be used to complete a variety of daily tasks. Until now, however, BCIs successful in controlling robotic arms have used invasive brain implants. These implants require a substantial amount of medical and surgical expertise to correctly install and operate, not to mention cost and potential risks to subjects, and as such, their use has been limited to just a few clinical cases. A grand challenge in BCI research is to develop less invasive or even totally noninvasive technology that would allow paralyzed patients to control their environment or robotic limbs using their own "thoughts." Such noninvasive BCI technology, if successful, would bring such much needed technology to numerous patients and even potentially to the general population. However, BCIs that use noninvasive external sensing, rather than brain implants, receive "dirtier" signals, leading to current lower resolution and less precise control. Thus, when using only the brain to control a robotic arm, a noninvasive BCI doesn't stand up to using implanted devices. Despite this, BCI researchers have forged ahead, their eye on the prize of a less- or non-invasive technology that could help patients everywhere on a daily basis. Bin He, Trustee Professor and Department Head of Biomedical Engineering at Carnegie Mellon University, is achieving that goal, one key discovery at a time. "There have been major advances in mind controlled robotic devices using brain implants. It's excellent science," says He. "But noninvasive is the ultimate goal. Advances in neural decoding and the practical utility of noninvasive robotic arm control will have major implications on the eventual development of noninvasive neurorobotics." Using novel sensing and machine learning techniques, He and his lab have been able to access signals deep within the brain, achieving a high resolution of control over a robotic arm. With noninvasive neuroimaging and a novel continuous pursuit paradigm, He is overcoming the noisy EEG signals leading to significantly improve EEG-based neural decoding, and facilitating real-time continuous 2D robotic device control. Using a noninvasive BCI to control a robotic arm that's tracking a cursor on a computer screen, for the first time ever, He has shown in human subjects that a robotic arm can now follow the cursor continuously. Whereas robotic arms controlled by humans noninvasively had previously followed a moving cursor in jerky, discrete motions -- as though the robotic arm was trying to "catch up" to the brain's commands -- now, the arm follows the cursor in a smooth, continuous path. In a paper published in Science Robotics, the team established a new framework that addresses and improves upon the "brain" and "computer" components of BCI by increasing user engagement and training, as well as spatial resolution of noninvasive neural data through EEG source imaging.
Cornell engineers have constructed a DNA material with capabilities of metabolism, in addition to self-assembly and organization – three key traits of life. As a genetic material, DNA is responsible for all known life. But DNA is also a polymer. Tapping into the unique nature of the molecule, Cornell engineers have created simple machines constructed of biomaterials with properties of living things. Using what they call DASH (DNA-based Assembly and Synthesis of Hierarchical) materials, Cornell engineers constructed a DNA material with capabilities of metabolism, in addition to self-assembly and organization – three key traits of life. “We are introducing a brand-new, lifelike material concept powered by its very own artificial metabolism. We are not making something that’s alive, but we are creating materials that are much more lifelike than have ever been seen before,” said Dan Luo, professor of biological and environmental engineering in the College of Agriculture and Life Sciences. The paper, “Dynamic DNA Material With Emergent Locomotion Behavior Powered by Artificial Metabolism,” is published April 10 2019 in Science Robotics.
Researchers from Chongqing University, in China, have recently developed a self-powered triboelectric auditory sensor (TAS) that could be used to build electronic auditory systems for external hearing aids in intelligent robotics applications. Their recent study, published in Science Robotics, could inform the creation of a new generation of auditory systems, addressing some of the key challenges in the field of social robotics. The auditory system is the most straightforward and effective means of communication between human beings and robots. Ideally, robotic auditory systems should allow robots to listen to human instructions while also perceiving their vocal intonations, in order to respond accordingly. One of the key aims of social robotics is hence to design auditory sensors that are powerful and sensitive in a wide frequency range. These applications could also benefit the 10 percent of the global population that have hearing impairments. "Commonly, people with impaired hearing always lose one or several specific frequency regions," the researchers who carried out the study told Tech Xplore. "The purpose of external hearing aids is to amplify the specific impaired sound regions to the audible level for those people. Therefore, the use of auditory sensors with frequency selectivity as hearing aid devices for recovering impaired hearing would enhance human-robot social interactions." An additional challenge within the field of robotics is related to power and energy. To successfully design auditory sensors with broadband frequency response and frequency selectivity, researchers should use traditional acoustic sensors with precise signal processing circuits, which raise the power consumption and reduce the working period.
Motion is a common phenomenon in biological processes. Major advances have been made in designing various self-propelled micromachines that harvest different types of energies into mechanical movement to achieve biomedicine and biological applications. Inspired by fascinating self-organization motion of natural creatures, the swarming or assembly of synthetic micro/nanomachines (often referred to micro/nanoswimmers, micro/nanorobots, micro/nanomachines, or micro/nanomotors), are able to mimic these amazing natural systems to help humanity accomplishing complex biological tasks. This review described the fuel induced methods (enzyme, hydrogen peroxide, hydrazine, et al.) and fuel-free induced approaches (electric, ultrasound, light, and magnetic) that led to control the assembly and swarming of synthetic micro/nanomachines. Such behavior is of fundamental importance in improving our understanding of self-assembly processes that are occurring on molecular to macroscopic length scales.
A research team has developed a mechanism of a self-propelled catheter capable of generating peristaltic motion just like an earthworm by applying pneumatic pressure inside only one tube. The goal is to develop an AutoGuide robot that propels itself inside bronchi, automatically reaching the target lesion within the lungs, and can take a lesion sample and provide treatment. Biopsies of pulmonary lesions are essential for increasing the accuracy of diagnosis and treatment for respiratory illnesses such as lung cancer. Currently, manual biopsies are performed via bronchoscopy. However, the bronchi tends to branch thinner and more complicatedly as it goes to the periphery, which makes it a challenge to reliably choose one and fine-tune the propelling movement. Given the skill disparities in operating doctors as well, it is difficult to reliably reach the lesion with the biopsy forceps, resulting in inadequate diagnosis accuracy. The development of instruments and mechanisms that can reliably reach the target in the lungs is required for adequately testing with an endoscope, but the looming challenge was finding a mechanism to reliably advance the biopsy forceps to the target even inside the ultrafine and widely branching bronchi. Now, Prof. Yuichiro Takai of Department of Respiratory Medicine, Omori Medical Center at Toho University and Prof. Hideyuki Tsukagoshi, of Department of System and Control Engineering at Tokyo Tech collaborate in developing the new self-propelled catheter designed to generate traveling waves in multiple chambers just by adding and reducing pressure inside one tube. This allowed for moving forward with peristaltic motion within an ultrafine structure such as a bronchus. This catheter also has an actively curving function for choosing the direction of propulsion, and a flexing drive function for adjusting to changes in line diameter. Their effectiveness was verified using a bronchus model. The goal is to increase the accuracy of branches which can be propelled, include a camera to collect information on the inside of the bronchi, develop functions applicable to biopsies and treatment, and put instruments to practical use.
Drones are getting tinier, cheaper, and will start swarming in huge groups like flocks of birds. These automated, flying robots are tiny, cheap, disposable. And in large groups, they could either save your life, or be the deadliest weapon since the machine gun. Earlier this year, 300 drones assembled into an American flag in Lady Gaga’s Super Bowl halftime show, illuminating the night sky. And Intel is promoting their Shooting Star swarms as an alternative to fireworks. Chinese company eHang claimed the record for the biggest swarm, in a spectacular New Year show in which 1,000 drones formed a map of China and the Chinese character for 'blessings'. Swarms could also check pipelines, chimneys, power lines and industrial plants cheaply and easily. Drone swarms may even have a place on the farm. They can spot plant disease and help manage water use, or spray pesticides and herbicides only in the exact spot needed, all working cooperatively to cover the area and fill in gaps. Nikolaos Papanikolopoulos of the Centre for Distributed Robotics at the University of Minnesota is working on solar-powered drones that will ultimately work together to survey large swathes of farmland at low cost. “Their roles may include early detection of nitrogen deficiency, plant disease, and proper management of water resources,” says Papanikolopoulos. Even the military is developing swarm technology. The US, for example, recently launched 103 small ‘Perdix’ drones from F/A-18 jets. These weigh a few hundred grams, and are released from dispensers normally used for flares. The 3D-printed Perdix drones are disposable, and are intended to suppress enemy air defences by acting as decoys or jammers or by locating radar so they can be destroyed. The US Navy also aims to develop a swarm of drones that costs less than a missile. It’s developing software that allows sub-swarms to be split off for particular missions, or fresh drones to join the swarm seamlessly. Another player is China, long the leader in small consumer drones. Chinese company DJI alone has around 70% of the global market, and now the Chinese military is seeing what they can do with this new technology. At an aerospace exhibition in December, state-owned China Electronics Technology Group Corporation (CETC) displayed a video of nearly 70 drones flying together. The drones flew in formation and collaborated in an intelligence-gathering mission. Those drones could also cooperate in a ‘saturation attack’ on an enemy missile launcher. They all dive in to attack simultaneously from different directions – far too many at once for the defenders to stop.
Via TechinBiz
From oil rigs to farms, more of the country's workplaces than ever are now welcoming robotic laborers. That spells lower costs for the companies that employ them, but it could be an awkward moment for the new president, whose pro-business stance and "America first" populism will have to contend with the fact that many of the machines will be made in China. Robots have a long track record of piecing together complex products like cars and consumer electronics. As their role in factory settings continues to expand, they are also now being used in more unpredictable settings. Bloomberg reports, for example, that oil drilling sites are becoming increasingly automated, with robots taking over the job of joining heavy pipes as they’re driven into wells. One oil company says that wells that previously required 20 employees may soon need as few as five. Meanwhile, the rising price of workers is driving some farmers of labor-intensive crops—such as fresh fruits and vegetables—to adopt robots. As both Forbes and Bloomberg report, the devices can currently be used to pick crops or thin out seedlings, and, despite their high upfront costs, don’t demand a minimum wage. The mining industry is undergoing similar changes, and even construction sites may soon get a robotic helping hand. It all sounds like a lot of jobs are at stake. And it’s certainly true that many traditional roles will be lost to robots. But as a recent report suggested, it will probably be a while yet before robots gobble up jobs en masse. Instead, the U.S. might choose to worry about where these robots actually come from. As Farhad Manjoo points out in the New York Times, many of the machines that will be used to automate jobs in America will come from China. The U.S. hasn’t invested heavily in building commercial robots, while China has been busy building an army of them.
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