Simultaneous Evolutionary-Based Optimization of Controller and Morphology of Snake-Like Modular Robots

Abstract

This paper explores the use of evolutionary algorithm approach to automatically design and optimize the snake-like modular robot to automatically design and optimize the snake-like modular robot to acquire the forward moving behaviour. A hybridized Genetic Programming and selfadaptive Differential Evolution algorithm is implemented to co-evolving both the morphology and controller of the robot throughout the artificial evolutionary process. Two different artificial evolutionary experiments have been conducted in this paper by using the classic DE mutation technique (DE/rand/1/bin) and a customized DE mutation technique with different mutation differential operation. It was found out that the customized DE mutation approach is more effective in coevolving both the morphology and controller for the snake-like modular robot to acquire forward moving behaviour. Moreover, from the analysis conducted on the results obtained throughout the evolutionary process, interesting findings were discovered on the evolved morphology and moving behaviour of the snake-like modular robot. In conclusion, promising results were shown in this work which suggests that the coevolving evolutionary algorithm presented in this work is an alternative method and feasible to be implemented to automatically design and optimize the modular robot for the moving behaviour by co-evolving both the morphology and controller of the modular robot.