A cerebellar approach to adaptive locomotion for legged robots
نویسندگان
چکیده
This paper describes a neural learning architecture for control of legged robots inspired by mammalian neurophysiology. Biological studies indicate that the cerebel-lum is a key part of an adaptive control system which enables mammals to display remarkable limb coordination during loco-motion. We present a distributed control system using reinforcement learning methods and mechanisms inspired by the cerebellum. Embedded within a framework of base locomotion controllers, the system is tasked with learning modulatory control signals which optimize gait performance measures. We brieey describe simulation studies in progress for a four-legged robot.
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