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Using your body to control a drone is more effective than a joystick. If you've ever been chastised for throwing your entire body around during gaming (because physically leaning into track corners definitely helps somehow), here's a bit of science-backed vindication. Researchers in Switzerland have discovered that using your torso to control a drone is far more effective than using a joystick. The team from EPFL monitored the body movements and muscular activity of 17 people, each with 19 markers placed all over their upper bodies. The participants then followed the actions of a virtual drone through simulated landscapes, via virtual reality goggles. By observing motion patterns, the scientists found that only four markers located on the torso were needed to pilot a drone through an obstacle course and that the method outperformed joystick control in both precision and reliability. The study's lead author, Jenifer Miehlbradt of EPFL's Translational Neuroengineering Laboratory, said: "Using your torso really gives you the feeling that you are actually flying. Joysticks, on the other hand, are of simple design but mastering their use to precisely control distant objects can be challenging." The proof-of-concept system still depends on body markers and external motion detectors to work, so the team's next challenge will be making the tech wearable and completely independent. However, the range of applications for it is enormous. Being able to virtually fly while your head, limbs, hand and feet are free to perform other tasks could be a major development for gaming, drone control or even the planes of the future. Content gathered by BTM robotics training centre, robotics in Bangalore, stem education in Bangalore, stem education in Bannerghatta road, stem education in JP Nagar, robotics training centres in Bannerghatta road, robotics training centres in JP Nagar, robotics training for kids, robotics training for beginners, best robotics in Bangalore,
'Blind' Cheetah 3 robot can climb stairs littered with obstacles. MIT's Cheetah 3 robot can now leap and gallop across rough terrain, climb a staircase littered with debris, and quickly recover its balance when suddenly yanked or shoved, all while essentially blind. The 90-pound mechanical beast -- about the size of a full-grown Labrador -- is intentionally designed to do all this without relying on cameras or any external environmental sensors. Instead, it nimbly "feels" its way through its surroundings in a way that engineers describe as "blind locomotion, " much like making one's way across a pitch-black room. "There are many unexpected behaviours the robot should be able to handle without relying too much on vision, " says the robot's designer, Sangbae Kim, associate professor of mechanical engineering at MIT. "Vision can be noisy, slightly inaccurate, and sometimes not available, and if you rely too much on vision, your robot has to be very accurate in position and eventually will be slow. So we want the robot to rely more on tactile information. That way, it can handle unexpected obstacles while moving fast." Researchers will present the robot's vision-free capabilities in October at the International Conference on Intelligent Robots, in Madrid. In addition to blind locomotion, the team will demonstrate the robot's improved hardware, including an expanded range of motion compared to its predecessor Cheetah 2, that allows the robot to stretch backwards and forwards, and twist from side to side, much like a cat limbering up to pounce. Within the next few years, Kim envisions the robot carrying out tasks that would otherwise be too dangerous or inaccessible for humans to take on. "Cheetah 3 is designed to do versatile tasks such as power plant inspection, which involves various terrain conditions including stairs, curbs, and obstacles on the ground, " Kim says. "I think there are countless occasions where we [would] want to send robots to do simple tasks instead of humans. Dangerous, dirty, and difficult work can be done much more safely through remotely controlled robots." Making a commitment The Cheetah 3 can blindly make its way up staircases and through unstructured terrain, and can quickly recover its balance in the face of unexpected forces, thanks to two new algorithms developed by Kim's team: a contact detection algorithm, and a model-predictive control algorithm. The contact detection algorithm helps the robot determine the best time for a given leg to switch from swinging in the air to stepping on the ground. For example, if the robot steps on a light twig versus a hard, heavy rock, how it reacts -- and whether it continues to carry through with a step, or pulls back and swings its leg instead -- can make or break its balance. "When it comes to switching from the air to the ground, the switching has to be very well-done, " Kim says. "This algorithm is really about, 'When is a safe time to commit my footstep?'" The contact detection algorithm helps the robot determine the best time to transition a leg between swing and step, by constantly calculating for each leg three probabilities: the probability of a leg making contact with the ground, the probability of the force generated once the leg hits the ground, and the probability that the leg will be in midswing. The algorithm calculates these probabilities based on data from gyroscopes, accelerometers, and joint positions of the legs, which record the leg's angle and height with respect to the ground. If, for example, the robot unexpectedly steps on a wooden block, its body will suddenly tilt, shifting the angle and height of the robot. That data will immediately feed into calculating the three probabilities for each leg, which the algorithm will combine to estimate whether each leg should commit to pushing down on the ground, or lift up and swing away in order to keep its balance -- all while the robot is virtually blind. "If humans close our eyes and make a step, we have a mental model for where the ground might be, and can prepare for it. But we also rely on the feel of touch of the ground, " Kim says. "We are sort of doing the same thing by combining multiple [sources of] information to determine the transition time." The researchers tested the algorithm in experiments with the Cheetah 3 trotting on a laboratory treadmill and climbing on a staircase. Both surfaces were littered with random objects such as wooden blocks and rolls of tape. "It doesn't know the height of each step and doesn't know there are obstacles on the stairs, but it just ploughs through without losing its balance, " Kim says. "Without that algorithm, the robot was very unstable and fell easily." Future force The robot's blind locomotion was also partly due to the model-predictive control algorithm, which predicts how much force a given leg should apply once it has committed to a step. "The contact detection algorithm will tell you, 'this is the time to apply forces on the ground, '" Kim says. "But once you're on the ground, now you need to calculate what kind of forces to apply so you can move the body in the right way." The model-predictive control algorithm calculates the multiplicative positions of the robot's body and legs a half-second into the future if a certain force is applied by any given leg as it makes contact with the ground. "Say someone kicks the robot sideways, " Kim says. "When the foot is already on the ground, the algorithm decides, 'How should I specify the forces on the foot? Because I have an undesirable velocity on the left, so I want to apply a force in the opposite direction to kill that velocity. If I apply 100 newtons’s in this opposite direction, what will happen a half second later?" The algorithm is designed to make these calculations for each leg every 50 milliseconds, or 20 times per second. In experiments, researchers introduced unexpected forces by kicking and shoving the robot as it trotted on a treadmill, and yanking it by the leash as it climbed up an obstacle-laden staircase. They found that the model-predictive algorithm enabled the robot to quickly produce counter-forces to regain its balance and keep moving forward, without tipping too far in the opposite direction. "It's thanks to that predictive control that can apply the right forces on the ground, combined with this contact transition algorithm that makes each contact very quick and secure, " Kim says. The team had already added cameras to the robot to give it visual feedback of its surroundings. This will help in mapping the general environment and will give the robot a visual heads-up on larger obstacles such as doors and walls. But for now, the team is working to further improve the robot's blind locomotion "We want a very good controller without vision first, " Kim says. "And when we do add vision, even if it might give you the wrong information, the leg should be able to handle (obstacles). Because what if it steps on something that a camera can't see? What will it do? That's where blind locomotion can help. We don't want to trust our vision too much." This research was supported, in part, by Naver, Toyota Research Institute, Foxconn, and Air Force Office of Scientific Research. Content gathered by BTM robotics training center, robotics in Bangalore, stem education in Bangalore, stem education in Bannerghatta road, stem education in JP nagar, robotics training centers in Bannerghatta road, robotics training centers in JP nagar, robotics training for kids, robotics training for beginners, best robotics in Bangalore,
Sprawling Wheel Leg Robot Crawls and Climbs. The latest version of this skittery little sprawling robot can crawl like a turtle. We’re always impressed by the way David Zarrouk (a professor at Ben-Gurion University of the Negev by way of UC Berkeley’s Biomimetic Mill systems Lab) manages to extract a ton of functionality from the absolute minimum of hardware in his robots. In the past, we’ve seen clever designs like a steerable robot that only uses a single motor and a multi-jointed robot arm that uses a travelling motor to actuate all of its degrees of freedom. At the 2018 IEEE International Conference on Robotics and Automation (ICRA) in Brisbane, Zarrouk presented an update to STAR, the Sprawl-Tuned Autonomous Robot that we first wrote about in 2013. Called Rising STAR, or RSTAR, it takes the sprawling wheel-leg mobility and adds another degree of freedom that allows the body of the robot to move separately from the legs, changing its centre of mass to help it climb over obstacles. RSTAR is the latest in Zarrouk’s series of sprawling robots, designed to handle all kinds of terrain obstacles while minimizing the cost of transport. “Sprawl” in this context refers to the robot’s legs, which are angled (adjustably) downwards and outwards from the body. RSTAR has an added degree of freedom in that its body is able to change its location relative to the legs, altering the robot’s centre of mass. It seems like a simple change, but it enables a bunch of new behaviours—not only can the robot climb over larger obstacles without flipping over, but it can also climb vertically up closely spaced walls and “crawl” through narrow gaps by adopting a legged walking gait. While the adjustable centre of mass helps keep the robot more stable, as the video shows flipping over can actually be useful, since it enables the robot to switch between faster and more efficient round wheels and more capable spoke wheels (whegs). RSTAR’s top speed is about 1 m/s on hard flat surfaces, although its turtle gait means that it can handle extremely soft or granular surfaces (like thick mud or sand) without getting stuck. Content gathered by BTM robotics training centre, robotics in Bangalore, stem education in Bangalore, stem education in Bannerghatta road, stem education in JP Nagar, robotics training centres in Bannerghatta road, robotics training centres in JP Nagar, robotics training for kids, robotics training for beginners, best robotics in Bangalore,
Firefighting Robot Snake Flies on Jets of Water. Using steerable jets of water like rockets, this robot snake can fly into burning buildings to extinguish fires. Fires have an unfortunate habit of happening in places that aren’t necessarily easy to reach. Whether the source of the fire is somewhere deep within a building, or up more than a floor or two, or both, firefighters have few good options for tackling them. They can either pour water into windows (which doesn’t always work that well), or they can try and get into the building, which seems like it’s probably super dangerous. At the International Conference on Robotics and Automation last month, researchers from Tohoku University and National Institute of Technology, Hachinohe College, in Japan, presented a new kind of snake-like robot with the body of a fire house. Like other snake robots, this one has the potential to be able to wiggle its way into windows or other gaps in a structure, with the benefit of carrying and directing water as it goes. What’s so cool about this particular design, though, is how it powers itself: By firing high pressure jets of water downwards like rocket engines, it can lift itself off of the ground and fly. What’s happening here might be complex to implement in practice, but in principle, it’s not too complicated: There are sets of steerable nozzle modules distributed along the length of the hose. These modules siphon water out of the high pressure stream inside of the hose, and spray it downwards. As the water exits downwards at high velocity, it pushes the hose upwards, and with enough of these modules squirting out high pressure water, the entire hose can be lifted into the air. Just like a rocket, it’s not dependent on ground proximity to work, so as long as you keep on giving it more hose and water at a high enough pressure, it’ll go as high as you want. Since the nozzles are steerable, each module can direct itself independently, letting the hose weave itself through small gaps deep into a structure in order to find the source of a fire. And the “head” module comes with a few extra degrees of freedom to allow the water stream to be directed more precisely. And of course, while the head nozzle is fighting the source of the fire, a byproduct of the body of the house keeping itself airborne is that it’s drenching everything that it’s passing over, while also keeping itself cool. The 2-meter long prototype in the video above is intended to be a single segment in a robot that can be extended to an arbitrary length by just adding on more segments. A gas engine powered a compressor that provided water at 0.7 MPa. It worked reasonably well, as prototypes go, but it’s really more of a proof of concept in hardware than anything else, and obviously there’s a lot to do before a system like this could be real-world useful. The researchers readily admit that their current control algorithms are “not sophisticated, ” and that they’ll need to put some work into making it more stable, more controllable, and able to handle more modules. They’re actively working on it, though, and we’re looking forward to this tech being adapted to garden hoses as well. Content gathered by BTM robotics training center, robotics in Bangalore, stem education in Bangalore, stem education in Bannerghatta road, stem education in JP nagar, robotics training centers in Bannerghatta road, robotics training centers in JP nagar, robotics training for kids, robotics training for beginners, best robotics in Bangalore,
Therapy Robot Teaches Social Skills to Children with Autism For some children with autism, interacting with other people can be an uncomfortable, mystifying experience. Feeling overwhelmed with face-to-face interaction, such children may find it difficult to focus their attention and learn social skills from their teachers and therapists—the very people charged with helping them learn to socially adapt. What these children need, say some researchers, is a robot: a cute, tech-based intermediary, with a body, that can teach them how to more comfortably interact with their fellow humans. On the face of it, learning human interaction from a robot might sound counter-intuitive. Or just backward. But a handful of groups are studying the technology in an effort to find out just how effective these robots are at helping children with autism spectrum disorder (ASD). One of those groups is LuxAI, a young company spun out of the University of Luxembourg. The company says its QTrobot can actually increase these children’s willingness to interact with human therapists, and decrease discomfort during therapy sessions. University of Luxembourg researchers working with QTrobot plan to present their results on 28 August at RO-MAN 2018, IEEE’s international symposium on robot and human interactive communication, held in Nanjing, China. “When you are interacting with a person, there are a lot of social cues such as facial expressions, tonality of the voice, and movement of the body which are overwhelming and distracting for children with autism, ” says Aida Nazarikhorram, co-founder of LuxAI. “But robots have this ability to make everything simplified, ” she says. “For example, every time the robot says something or performs a task, it’s exactly the same as the previous time, and that gives comfort to children with autism.” Feeling at ease with a robot, these children are better able to focus their attention on a curriculum presented together by the robot and a human therapist, Nazarikhorram says. In the study that will presented at RO-MAN later this month, 15 boys ages 4 to 14 years participated in two interactions: one with QTrobot and one with a person alone. The children directed their gaze toward the robot about twice as long, on average, compared with their gaze toward the human. Repetitive behaviors like hand flapping—a sign of being uncomfortable and anxious—occurred about three times as often during sessions with the human, compared with the robot, according to the study. More importantly, with a robot in the room, children tend to interact more with human therapists, according to feedback the company received during its research, says Nazarikhorram. “The robot has the ability to create a triangular interaction between the human therapist, the robot, and the child, ” she says. “Immediately the child starts interacting with the educator or therapist to ask questions about the robot or give feedback about its behavior.” A number of groups have been developing digital therapeutics to treat psychiatric disorders, such as apps to treat substance abuse, and therapeutic video games to treat attention deficit/hyperactivity disorder. But there’s something about the embodied robot that gives it an edge over plain screens. “The child is just focused on the app and doesn’t interact with the person beside him, ” Nazarikhorram says. “With a robot, it’s the opposite.” Robot-based therapy for autism has been studied for more than a decade. For instance, scientists first conceived of KASPAR the social robot in the late 1990s. It is now being developed by scientists at the University of Hertfordshire in the United Kingdom. And there are at least two other commercial robots for autism: Robokind’s Milo and Softbank Robotics’ NAO. The MIT Media Lab recently used NAO to test a machine learning network it built that is capable of perceiving children’s behavior. The algorithm can estimate the level of interest and excitement of children with autism during a therapy session. The research was published in June in Science Robotics. “In the end, we want the robots to be a medium towards naturalistic human-human interactions and not solely tools for capturing the attention of the kids, ” says Oggi Rudovic, at the MIT Media Lab, who co-authored the machine learning paper in Science Robotics. The ultimate goal is to equip children with autism “with social skills that they can apply in everyday life, ” he says, and LuxAI’s research “is a good step towards that goal.” However, more research, involving more children over longer periods of time, will be needed to assess whether robots can really equip children with real-life social skills, Rudovic says. The QTrobot is a very new product. LuxAI started building it in 2016, finished a final prototype in mid-2017, and just this year began trials at various centers in Luxembourg, France, Belgium, and Germany. Nazarikhorram says she wanted to build a robot that was practical for classrooms and therapy settings. Her company focused on making its robot easily programmable by autism professionals with no tech background, and able to run for hours without having to be shut down to cool. It also has a powerful processor and 3D camera so that no additional equipment, such as a laptop, is needed, she says. Now LuxAI is conducting longer-term trials, studying the robot’s impact on social competence, emotional well-being, and interaction with people, Nazarikhorram says. We asked Nazarikhorram if it’s possible that pairing robots with children with autism could actually move them further away from people, and closer to technology. “That’s one of the fears that people have, ” she says. “But in practice, in our studies and based on the feedback of our users, the interaction between the children and the therapists improves.” Content gathered by BTM robotics training center, robotics in Bangalore, stem education in Bangalore, stem education in Bannerghatta road, stem education in JP Nagar, robotics training centers in Bannerghatta road, robotics training centers in JP Nagar, robotics training for kids, robotics training for beginners, best robotics in Bangalore
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