Optimization of Snake-like Robot Locomotion Using GA: Serpenoid Design

This work investigates the locomotion efficiency of snake-like robots through evolutionary optimization using the simulation framework PhysX (NVIDIA). The Genetic Algorithm (GA) is used to find the optimal forward head serpentine gait parameters, and the snake speed is taken into consideration in the optimization. A fitness function covering robot speed is based on a complex physics simulation in PhysX. A general serpenoid form is applied to each joint. Optimal gait parameters are calculated for a virtual model in a simulation environment. The fitness function evaluation uses the Simulation In the Loop (SIL) technique, where the virtual model is an approximation of a real snake-like robot. Experiments were performed using an 8-link snake robot with a given mass and a different body friction. The aim of the optimization was speed and length of the trace.

Keywords

Snake-like robot, serpenoid curve, genetic algorithm, physical simulation, PhysX

Citation

Mendel. 2020 vol. 26, č. 1, s. 1-6. ISSN 1803-3814
https://mendel-journal.org/index.php/mendel/article/view/113

Document type

Peer-reviewed

Document version

Published version

Language of document

en

Document licence

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International license
http://creativecommons.org/licenses/by-nc-sa/4.0