Optimizing Robotic Cheetah Leg Parameters Using Evolutionary Algorithms

Maxim Buzdalov, Sergey Kolyubin, Artem Egorov, Ivan Borisov

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)


We present a new application suitable for evolutionary algorithms: geometry optimization for robotic applications. Our working example is a robotic cheetah leg, which uses simple control algorithms, but accurately crafted and tuned mechanics to maximize motion efficiency. In this paper we aim at tuning its parameters, such that the joints of the leg follow the desired trajectories as close as possible. Optimization is done in two stages involving just two parameters each.

Even this simply-looking problem presents a challenge to evolutionary algorithms, as it is both ill-conditioned and multimodal. However, we show that choosing a better fitness function that captures our desires in a different way can make the problem much easier.
Original languageEnglish
Title of host publicationBioinspired Optimization Methods and Their Applications - 9th International Conference, BIOMA 2020, Proceedings
Subtitle of host publication9th International Conference, BIOMA 2020, Brussels, Belgium, November 19–20, 2020, Proceedings
EditorsBogdan Filipic, Edmondo Minisci, Massimiliano Vasile
PublisherSpringer Nature
Number of pages14
ISBN (Electronic)978-3-030-63710-1, 3030637107
ISBN (Print)9783030637095, 3030637093
Publication statusPublished - 16 Nov 2020
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12438 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


  • Fitness function
  • Multimodal functions
  • Robotic leg


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