Open AccessOPTIMIZING A QUADRUPED ROBOT: A COMPARISON OF TWO METHODS
Author(s) -
Robert Α. Pastor,
Zdenko Bobovský,
Petr Oščádal,
Jakub Měsíček,
Marek Pagáč,
Erik Prada,
Ľubica Miková,
Ján Babjak
Publication year - 2021
Publication title -
mm science journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.195
H-Index - 10
eISSN - 1805-0476
pISSN - 1803-1269
DOI - 10.17973/mmsj.2021_6_2021008
Subject(s) - robot , genetic algorithm , computer science , topology (electrical circuits) , topology optimization , simulation , artificial intelligence , engineering , machine learning , structural engineering , electrical engineering , finite element method
Robots that have been optimized in simulation often underperform in the real world in comparison to their simulated counterparts. This difference in performance is often called a reality-gap. In this paper, we use two methods, genetic algorithm and topology optimization, to optimize a quadruped robot. We look at the original and optimized robots’ performance in simulation and reality and compare the results. Both methods show improvement in the robot’s efficiency, however the topology optimization behaves in a more predictable manner and shows similar results in simulation and in real laboratory testing. Modifying robot morphology with a genetic algorithm, although less predictable, has a potential for more improvement in efficiency.