Learning Robot-Environment Interaction Using Echo State Networks

Learning robot-environment interaction with echo state networks (ESNs) is presented in this paper. ESNs are asked to bootstrap a robot’s control policy from human teacher’s demonstrations on the robot learner, and to generalize beyond the demonstration dataset. Benefits and problems involved in some navigation tasks are discussed, supported by real-world experiments with a small mobile robot.

• Type: Journal
• Year: 2010
• Where: SAB
• Authors: Mohamed Oubbati, Bahram Kord, Günther Palm
• Keywords: Echo State Networks, Optimization, Robot’s Control Policy, SAB 2010, Small Mobile Robot