Robot control by learning and recalling of temporal patterns in chaos neural network

摘要

For controlling un-modeled distributed reconfigurabel robots, the controller should learn a sequence of actuator commands, considering the perceptual aliasing problem. We introduce the chaos neural network for a basic learning module, then we propose a learning algorithm of the temporal pattern through the trial and error, and demonstrate it with simulations of a net-shape robot.