Comparative stable walking gait optimization for small-sized biped robot using meta-heuristic optimization algorithms

Tran Thien Huan, Ho Pham Huy Anh
<span title="2018-12-27">2018</span> <i title="Publishing House for Science and Technology, Vietnam Academy of Science and Technology"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gnzwobprrzci3e4ywwaz7gkkpe" style="color: black;">Vietnam Journal of Mechanics</a> </i> &nbsp;
This paper proposes a new way to optimize the biped walking gait design for biped robots that permits stable and robust stepping with pre-set foot lifting magnitude. The new meta-heuristic CFO-Central Force Optimization algorithm is initiatively applied to optimize the biped gait parameters as to ensure to keep biped robot walking robustly and steadily. The efficiency of the proposed method is compared with the GA-Genetic Algorithm, PSO-Particle Swarm Optimization and Modified Differential
more &raquo; ... tion algorithm (MDE). The simulated and experimental results carried on the prototype small-sized humanoid robot demonstrate that the novel meta-heuristic CFO algorithm offers an efficient and stable walking gait for biped robots with respect to a pre-set of foot-lift height value.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.15625/0866-7136/12294">doi:10.15625/0866-7136/12294</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nyuquzpobfhele726ocmqiqx4u">fatcat:nyuquzpobfhele726ocmqiqx4u</a> </span>
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