Optimized stable gait planning of biped robot using multi-objective evolutionary JAYA algorithm

Huan Tran Thien,Ho Pham Huy Anh,Cao Van Kien

doi:10.1177/1729881420976344

Abstract

This article proposes a new stable biped walking pattern generator with preset step-length value, optimized by multi-objective JAYA algorithm. The biped robot is modeled as a kinetic chain of 11 links connected by 10 joints. The inverse kinematics of the biped is applied to derive the specified biped hip and feet positions. The two objectives related to the biped walking stability and the biped to follow the preset step-length magnitude have been fully investigated and Pareto optimal front of solutions has been acquired. To demonstrate the effectiveness and superiority of proposed multi-objective JAYA, the results are compared to those of MO-PSO and MO-NSGA-2 optimization approaches. The simulation and experiment results investigated over the real small-scaled biped HUBOT-4 assert that the multi-objective JAYA technique ensures an outperforming effective and stable gait planning and walking for biped with accurate preset step-length value.

Highlights

Nowadays, humanoid robots have attracted the attention from numerous scientists.[1]
Survey the performance of MO-JAYA algorithm in optimization biped walking with preset step length and gait walking pattern generator (WPG) planning of biped robot by changing the population number of particles (NP)
These results show that the MO-JAYA technique attains the best optimization performance with NP 1⁄4 32

Summary

Introduction

Humanoid robots have attracted the attention from numerous scientists.[1] The fact is that biped robot research have frequently met with big obstacles in how to realize the humanlike locomotion and in how to effectively and efficiently control. On study of Kajita,[2] as to have biped to naturally walk, it needs a walking pattern generator (WPG) through which biped can realize the required step. WPG is created using zero moment point (ZMP) criteria in which it exists two principal design methods: the first relies on an inverse pendubot structure and the second improves from biped foot–hip trajectorial tracking. The first approach model is introduced by Kajita[3,4,5] in which numerous studies have investigated the 3D inverse pendubot as to use in stable biped control. The second model is initiatively proposed by Huang[6] in which various

Objectives

Results

Conclusion