Stable modifiable walking pattern algorithm with constrained optimized central pattern generator

Abstract

In this paper, stable modifiable walking pattern algorithm is proposed using evolutionary optimized central pattern generator (CPG). Sensory feedback pathways in CPG are proposed, which use force sensing resistor (FSR) signals. For the optimization of CPG parameters, two-phase evolutionary programming (TPEP) is employed. Modifiable walking pattern generator (MWPG) generates position trajectory of center of mass (COM) of humanoid robot and CPG generates sagittal swing foot position trajectory. The effectiveness of the proposed scheme is demonstrated by simulations using a Webots dynamic simulator for a small sized humanoid robot, HSR-IX, developed in the Robot Intelligence Technology (RIT) Lab, KAIST. © 2013 Springer-Verlag.