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July 9, 2021 by Sarah Yang Delivery services may be able to overcome snow, rain, heat and the gloom of night, but a new class of legged robots is not far behind. Artificial intelligence algorithms developed by a team of researchers from UC Berkeley, Facebook and Carnegie Mellon University are equipping legged robots with an enhanced ability to adapt to and navigate unfamiliar terrain in real time. Their test robot successfully traversed sand, mud, hiking trails, tall grass and dirt piles without falling. It also outperformed alternative systems in adapting to a weighted backpack thrown onto its top or to slippery, oily slopes. When walking down steps and scrambling over piles of cement and pebbles, it achieved 70% and 80% success rates, respectively, still an impressive feat given the lack of simulation calibrations or prior experience with the unstable environments.

United statesSarah yangJitendra malikAshish kumarDeepak pathakZipeng fuCarnegie mellon universityBerkeley ai researchUc berkeley department of electrical engineeringSchool of computer scienceComputer sciencesFacebook ai researchMotor adaptation enabledRapid motor adaptationElectrical engineeringComputer science