Optimizing Robotic Cheetah Leg Parameters Using Evolutionary Algorithms

Maxim Buzdalov; Sergey Kolyubin; Artem Egorov; Ivan Borisov

doi:10.1007/978-3-030-63710-1_17

Optimizing Robotic Cheetah Leg Parameters Using Evolutionary Algorithms

Maxim Buzdalov, Sergey Kolyubin, Artem Egorov, Ivan Borisov

ITMO University

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Trafodion Cynhadledd (Nid-Cyfnodolyn fathau)

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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.

Iaith wreiddiol	Saesneg
Teitl	Bioinspired Optimization Methods and Their Applications - 9th International Conference, BIOMA 2020, Proceedings
Is-deitl	9th International Conference, BIOMA 2020, Brussels, Belgium, November 19–20, 2020, Proceedings
Golygyddion	Bogdan Filipic, Edmondo Minisci, Massimiliano Vasile
Cyhoeddwr	Springer Nature
Tudalennau	214-227
Nifer y tudalennau	14
ISBN (Electronig)	978-3-030-63710-1, 3030637107
ISBN (Argraffiad)	9783030637095, 3030637093
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1007/978-3-030-63710-1_17
Statws	Cyhoeddwyd - 16 Tach 2020
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Enw	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Cyfrol	12438 LNCS
ISSN (Argraffiad)	0302-9743
ISSN (Electronig)	1611-3349

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10.1007/978-3-030-63710-1_17

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Buzdalov, M., Kolyubin, S., Egorov, A., & Borisov, I. (2020). Optimizing Robotic Cheetah Leg Parameters Using Evolutionary Algorithms. Yn B. Filipic, E. Minisci, & M. Vasile (Gol.), Bioinspired Optimization Methods and Their Applications - 9th International Conference, BIOMA 2020, Proceedings: 9th International Conference, BIOMA 2020, Brussels, Belgium, November 19–20, 2020, Proceedings (tt. 214-227). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Cyfrol 12438 LNCS). Springer Nature. https://doi.org/10.1007/978-3-030-63710-1_17

Buzdalov, Maxim ; Kolyubin, Sergey ; Egorov, Artem et al. / Optimizing Robotic Cheetah Leg Parameters Using Evolutionary Algorithms. Bioinspired Optimization Methods and Their Applications - 9th International Conference, BIOMA 2020, Proceedings: 9th International Conference, BIOMA 2020, Brussels, Belgium, November 19–20, 2020, Proceedings. Gol. / Bogdan Filipic ; Edmondo Minisci ; Massimiliano Vasile. Springer Nature, 2020. tt. 214-227 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Optimizing Robotic Cheetah Leg Parameters Using Evolutionary Algorithms",

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.",

keywords = "Fitness function, Multimodal functions, Robotic leg",

author = "Maxim Buzdalov and Sergey Kolyubin and Artem Egorov and Ivan Borisov",

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doi = "10.1007/978-3-030-63710-1_17",

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Buzdalov, M, Kolyubin, S, Egorov, A & Borisov, I 2020, Optimizing Robotic Cheetah Leg Parameters Using Evolutionary Algorithms. yn B Filipic, E Minisci & M Vasile (gol.), Bioinspired Optimization Methods and Their Applications - 9th International Conference, BIOMA 2020, Proceedings: 9th International Conference, BIOMA 2020, Brussels, Belgium, November 19–20, 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), cyfrol. 12438 LNCS, Springer Nature, tt. 214-227. https://doi.org/10.1007/978-3-030-63710-1_17

Optimizing Robotic Cheetah Leg Parameters Using Evolutionary Algorithms. / Buzdalov, Maxim; Kolyubin, Sergey; Egorov, Artem et al.
Bioinspired Optimization Methods and Their Applications - 9th International Conference, BIOMA 2020, Proceedings: 9th International Conference, BIOMA 2020, Brussels, Belgium, November 19–20, 2020, Proceedings. gol. / Bogdan Filipic; Edmondo Minisci; Massimiliano Vasile. Springer Nature, 2020. t. 214-227 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Cyfrol 12438 LNCS).

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Trafodion Cynhadledd (Nid-Cyfnodolyn fathau)

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Buzdalov M, Kolyubin S, Egorov A, Borisov I. Optimizing Robotic Cheetah Leg Parameters Using Evolutionary Algorithms. Yn Filipic B, Minisci E, Vasile M, golygyddion, Bioinspired Optimization Methods and Their Applications - 9th International Conference, BIOMA 2020, Proceedings: 9th International Conference, BIOMA 2020, Brussels, Belgium, November 19–20, 2020, Proceedings. Springer Nature. 2020. t. 214-227. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-63710-1_17

Optimizing Robotic Cheetah Leg Parameters Using Evolutionary Algorithms

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