Abstract

In this work, we present a practical approach for producing a stable 3D gallop in a simulated quadrupedal robot which includes the prominent characteristics of the biological gait. The dynamic model utilizes biologically-based assumptions, and the resulting 3D gallop contains the prominent biological features of early leg retraction, phase-locked leg motion, a significant gathered flight phase, unconstrained spatial dynamics, and a smooth gait. A multiobjective genetic algorithm is used to find control parameters in a partitioned search space. During stance, a simple energy control law ensures a fixed amount of energy in the knee springs during each stride, which is a key factor for stabilization.

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