Imagine a four-legged robotic system that can dribble a soccer ball under the same conditions as humans; a bot so smart that it uses a mixture of onboard sensing and computing to traverse different natural terrains such as sand, gravel, mud and snow, and adapt to their varied impact on the ball’s motion. Like every committed athlete, DribbleBot can get up and recover the ball after falling, getting better with every game. His potential, however, goes well beyond fun. “We need machines that can go over terrains that aren’t flat, especially in disaster and search-and-rescue scenarios, and wheeled robots can’t traverse those landscapes,” says Pulkit Agrawal, MIT Professor, CSAIL Principal Investigator & Director of Improbable AI Lab. “Our goal in developing algorithms for legged robots is to provide autonomy in challenging and complex terrains that are currently beyond the reach of robotic systems.”; EECS.MIT.edu.
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