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Ex-NASA Engineer Made the Perfect Rock Skipping Robot Ex-NASA engineer and YouTube inventor Mark Rober have made a perfect rock-skipping robot. Not only can the robot perform impressively, but it can help you learn how to skip rocks better too. Rober built the robot by tweaking a clay pigeon thrower, creating wooden custom throwing arms and a base for stability. Once he built a prototype, his team of assistants (nieces and nephews) gave Skippa, the rock-throwing robot makeover with spray paint and giant googly eyes, and then brainstormed test variables for a perfect skip. How do you achieve the perfect rock skip? The team narrowed it down to four variables: the wrist angle of the robot (the angle of the rock relative to the water), the arm angle of the robot (which changes the path of the rock), and the rocks used (variations in diameter and thickness). To create uniform controls for robot tests, Rober and his team made their own rocks out of unfired clay (the clay discs easily dried in the sun, and dissolved in water under 30 mins). After the robot tested some unsuccessful skips, it began to shoot rocks tumbling across the water in over 60 skips per throw. Here’s the recipe Rober finally found for the perfect rock skip: the rock should hit at a 20-degree angle to the water, with a 20-degree path, and a higher throw for more energy. Flicking the wrist as much as possible will help the rock spin, which will help the rock stable. And finally, the most important factors for rock selection is a flat bottom and finding a rock that’s heavy but not too big to handle. When Rober’s amateur engineering team tested the principles they learned from the robot, they were quickly able to improve their skips from an average of three to 16 skips. 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,
'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,
SAY HI TO CIMON, THE FIRST AI-POWERED ROBOT TO FLY IN SPACE. When you thought that Artificial Intelligence (AI) is redefining life on Earth, think again! Meet CIMON, the first AI-powered robot who was launched into space from Florida on Friday, June 29th to join the crew and assist astronauts of the International Space Station (ISS). CIMON was launched by a SpaceX rocket carrying food and supplies for the crew aboard the International Space Station. At CIMON’s pre-launch news conference, Kirk Shireman, NASA’s International Space Station (ISS) program manager, addressed that the knowledge base and ability to tap into AI in a way that is useful for the task that is done is really critical for having humans further and further away from the planet. CIMON or (Crew Interactive Mobile Companion) is programmed to answer voice commands in English. The AI-powered robot is roughly the size of a volleyball and weighs 5 kilograms. CIMON will float through the zero-gravity environment of the space station to research a database of information about the ISS. In addition to the mechanical tasks assigned, the AI-powered CIMON can even assess the moods of its human crewmates at the ISS and interact accordingly with them. An Intelligent Astronaut CIMON is the brainchild of the European aerospace company Airbus. With the artificial intelligence inside powered by IBM, AI-Powered CIMON was initially built for the German space agency. Alexander Gerst, a German astronaut currently aboard the ISS, assisted with the design of CIMON’s screen prompts and vocal controls. As per the mission description written by Airbus representatives, CIMON’s mission calls for the AI-Powered astronaut robot to work with Gerst on three separate investigations. Cimon’s tasks at ISS include experimenting with crystals, working together with Gerst to solve the Rubik’s cube and performing a complex medical experiment using itself as an ‘intelligent’ flying camera. CIMON can interact with anyone at ISS; the AI-powered robot will nod when any command is spoken in English. However, CIMON is programmed to specifically help Gerst during its first stay on the ISS. Alexander Gerst can make CIMON work by speaking commands in English like, ‘CIMON, could you please help me perform a certain experiment? or could you please help me with the procedure?'” In response, CIMON will fly towards Alexander Gerst, to start the communication. An Interactive Step Forward CIMON knows whom it is talking to through its inbuilt facial-recognition software. If you thought that CIMON would look like a mechanical robot, you are wrong. CIMON has a face of its own, a white screen with a smiley face. The astronaut AI assistant will be able to float around, by sucking air in and expelling it out through its special tubes once it is aboard the ISS. CIMON’s mission to space demonstrates researchers, the collaboration of humans and AI-powered technology for further explorations. However, it will be a long way before intelligent robots are ready to undertake principal tasks in the final frontier including helping astronauts repair damaged spacecraft systems or treating sick crewmembers. But a beginning has been made with CIMON and that day will probably be a reality soon. In its first space mission, CIMON will stay in space for a few months and is scheduled to return to earth in December. Post its return, scientists will study and assess its abilities for future implementations. With the launch of CIMON, a lifelong space-exploration association between humans and machine may have just begun. 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.
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