A new robotic locomotion model capable of real-time terrain adaptation has been developed by a multi-institutional research team.
Engineers at Facebook AI, the University of California, Berkeley (UC Berkeley), and Carnegie Mellon University based Rapid Motor Adaptation (RMA) on the ability of humans and animals to quickly and unconsciously adjust their locomotion to different conditions.
The team trained the system in a virtual model of the real world, where the robot's brain learned to maximize forward motion with the least amount of energy, and to avoid falls by responding to incoming data from physical sensors.
UC Berkeley's Jitendra Malik said the robot employs absolutely no visual input, instead closely monitoring itself.
The RMA system uses a constantly running main gait-control algorithm and a parallel adaptive algorithm that watches internal readings and provides the main model adjustment data in response to terrain changes.
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