Toward Intelligent Biped-Humanoids Gaits Generation

TL;DR

This paper presents a biologically inspired, intelligent gait generation method for humanoid robots using a hybrid particle swarm optimization algorithm based on human walking analysis.

Contribution

It introduces a novel hybrid algorithm for gait generation that mimics human walking mechanics, offering an alternative to traditional kinematic and dynamic methods.

Findings

Effective gait trajectories generated for humanoid robots.

Algorithm suitable for robots with at least six DOF.

Potential for improved naturalness in robot walking.

Abstract

In this chapter we will highlight our experimental studies on natural human walking analysis and introduce a biologically inspired design for simple bipedal locomotion system of humanoid robots. Inspiration comes directly from human walking analysis and human muscles mechanism and control. A hybrid algorithm for walking gaits generation is then proposed as an innovative alternative to classically used kinematics and dynamic equations solving, the gaits include knee, ankle and hip trajectories. The proposed algorithm is an intelligent evolutionary based on particle swarm optimization paradigm. This proposal can be used for small size humanoid robots, with a knee an ankle and a hip and at least six Degrees of Freedom (DOF).