Adaptive Four Legged Locomotion Control Based on Nonlinear Dynamical Systems

Dynamical systems have been increasingly studied in the last decade for designing locomotion controllers. They offer several advantages over previous solutions like synchronization, smooth transitions under parameter variation, and robustness. In this paper, we present an adaptive locomotion controller for four-legged robots. The controller is composed of a set of coupled nonlinear dynamical systems. Using our controller the robot is capable of adapting its locomotion to the physical properties of the robot, in particular its resonant frequency. Our approach aims at developing an on-line learning system that attempts to minimize the energy necessary for the gait. We have implemented the model both in a simulated physical environment (Webots) and on a Sony Aibo robot. We present a series of experiments which demonstrate how the controller can tune its frequency to the resonant frequency of the robot, and modify it when the weight of the robot is changed.