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Optimizing Robotic Cheetah Leg Parameters Using Evolutionary Algorithms

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Bioinspired Optimization Methods and Their Applications (BIOMA 2020)

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Abstract

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.

Supported by Russian Science Foundation grant (project no. 17-79-20341).

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Notes

  1. 1.

    https://github.com/CMA-ES/pycma.

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Correspondence to Maxim Buzdalov .

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Buzdalov, M., Kolyubin, S., Egorov, A., Borisov, I. (2020). Optimizing Robotic Cheetah Leg Parameters Using Evolutionary Algorithms. In: Filipič, B., Minisci, E., Vasile, M. (eds) Bioinspired Optimization Methods and Their Applications. BIOMA 2020. Lecture Notes in Computer Science(), vol 12438. Springer, Cham. https://doi.org/10.1007/978-3-030-63710-1_17

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  • DOI: https://doi.org/10.1007/978-3-030-63710-1_17

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