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- W3045568346 abstract "This paper presents a bio-inspired central pattern generator (CPG)-type architecture for learning optimal maneuvering control of periodic locomotory gaits. The architecture is presented here with the aid of a snake robot model problem involving planar locomotion of coupled rigid body systems. The maneuver involves clockwise or counterclockwise turning from a nominally straight path. The CPG circuit is realized as a coupled oscillator feedback particle filter. The collective dynamics of the filter are used to approximate a posterior distribution that is used to construct the optimal control input for maneuvering the robot. A Q-learning algorithm is applied to learn the approximate optimal control law. The issues surrounding the parametrization of the Q-function are discussed. The theoretical results are illustrated with numerics for a 5-link snake robot system." @default.
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- W3045568346 date "2020-07-01" @default.
- W3045568346 modified "2023-09-28" @default.
- W3045568346 title "Bio-inspired Learning of Sensorimotor Control for Locomotion" @default.
- W3045568346 doi "https://doi.org/10.23919/acc45564.2020.9147889" @default.
- W3045568346 hasPublicationYear "2020" @default.
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