Optimized stable gait planning of biped robot using multi-objective evolutionary JAYA algorithm. (14th December 2020)

• Record Type: Journal Article
• Authors: Tran Thien, Huan; Van Kien, Cao; Anh, Ho Pham Huy
• Is Part Of: International journal of advanced robotic systems. Volume 17:Number 6(2020:Nov./Dec.)
• Publication Date: 2020-12-14
• Subjects: Humanoid stable and robust walking -- walking pattern generator (WPG) -- multi-objective (MO) optimization method -- MO-NSGA-2 -- MO-PSO -- MO-JAYA optimization algorithm -- Pareto optimal front; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881420976344
• Languages: English
• ISSNs: 1729-8806

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.