When you combine robots and cheetahs with military funding, you’re bound to end up with something incredible. Robotics engineers from MIT have spent over five years developing a battery-powered quadruped robot capable of running as fast as a human being. MIT’s Cheetah robot has already beaten the speed record set by Usain Bolt (the world’s fastest man) and now it’s coming after Aries Merritt (the world’s fastest hurdler, of course). Researchers at the MIT have upgraded Cheetah with new algorithms that allow it to detect and jump over obstacles — the first four-legged robot to do so autonomously.
In a video released by the team from MIT shows off their DARPA-funded, four-legged harbinger of terror approaching and clearing obstacles up to 18 inches tall while maintaining an average speed of 5 mph. The 70-lb robot (roughly the same weight as a female cheetah) estimates the height, size, and distance of objects in its path, and adjusts its approach to prepare a jump and safe landing—all without slowing down.
MIT researchers have trained their robotic cheetah to see and jump over hurdles as it runs — making this the first four-legged robot to run and jump over obstacles autonomously. Credit: Haewon Park, Patrick Wensing, and Sangbae Kim (MIT)
“A running jump is a truly dynamic behavior,” says Sangbae Kim, an assistant professor of mechanical engineering at MIT. “You have to manage balance and energy, and be able to handle impact after landing. Our robot is specifically designed for those highly dynamic behaviors.” Kim and his colleagues—including research scientist Hae won Park and postdoc Patrick Wensing—will demonstrate their cheetah’s running jump at the DARPA Robotics Challenge in June, and will present a paper detailing the autonomous system in July at the conference Robotics: Science and Systems.
Last September, the group demonstrated that the robotic cheetah was able to run untethered—a feat that Kim notes the robot performed “blind,” without the use of cameras or other vision systems. Now, the robot can “see,” with the use of onboard LIDAR—a visual system that uses reflections from a laser to map terrain. The team developed a three-part algorithm to plan out the robot’s path, based on LIDAR data. Both the vision and path-planning system are onboard the robot, giving it complete autonomous control. The algorithm’s first component enables the robot to detect an obstacle and estimate its size and distance. The researchers devised a formula to simplify a visual scene, representing the ground as a straight line, and any obstacles as deviations from that line. With this formula, the robot can estimate an obstacle’s height and distance from itself.
Once the robot has detected an obstacle, the second component of the algorithm kicks in, allowing the robot to adjust its approach while nearing the obstacle. Based on the obstacle’s distance, the algorithm predicts the best position from which to jump in order to safely clear it, then backtracks from there to space out the robot’s remaining strides, speeding up or slowing down in order to reach the optimal jumping-off point. This “approach adjustment algorithm” runs on the fly, optimizing the robot’s stride with every step. The optimization process takes about 100 milliseconds to complete—about half the time of a single stride.
The team tested the MIT cheetah’s jumping ability first on a treadmill, then on a track. On the treadmill, the robot ran tethered in place, as researchers placed obstacles of varying heights on the belt. As the treadmill itself was only about 4 meters long, the robot, running in the middle, only had 1 meter in which to detect the obstacle and plan out its jump. After multiple runs, the robot successfully cleared about 70 percent of the hurdles.
In comparison, tests on an indoor track proved much easier, as the robot had more space and time in which to see, approach, and clear obstacles. In these runs, the robot successfully cleared about 90 percent of obstacles. Kim is now working on getting the MIT cheetah to jump over hurdles while running on softer terrain, like a grassy field. (Credit: MIT)
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