Particle swarm optimization algorithm vs. genetic algorithm to solve multi-objective optimization problem in gait planning of biped robot

Abstract

This paper deals with multi-objective optimization problems in ascending and descending gait planning of biped robot, which has been solved using particle swarm optimization algorithm and genetic algorithm separately. In order to model this problem, two modules of adaptive neuro-fuzzy inference systems have been adopted. Two contrasting objectives, such as power consumption and dynamic balance margin have been considered, and Pareto optimal front of solutions has been obtained. © 2012 Springer-Verlag GmbH Berlin Heidelberg.