Development of a genetic algorithm for the optimization of hexapod robot parameters

Abstract

Legged robots allow the locomotion on terrains inaccessible to other type of vehicles because they do not need a continuous support surface. Different strategies have been adopted for the optimization of these systems, during their design and construction phases, and during their operation. Among the different optimization criteria followed by different authors, it is possible to find issues related to energy efficiency, stability, speed, comfort, mobility and environmental impact. Evolutionary strategies are a way to ”imitate nature” replicating the process that nature designed for the generation and evolution of species. The objective of this paper is to present a genetic algorithm, running over a simulation application of legged robots, which allows the optimization of several parameters of the robot model and of its gaits, for different locomotion speeds.