Finding Proper Configurations for Modular Robots by Using Genetic Algorithm on Different Terrains
This paper presents a novel self-reconfigurable robotic system named ACMoD where each module can move itself individually. It can also attach to other modules to build various configurations and change this configuration adaptively on different terrains. In this paper, we have proposed Genetic Algorithm for optimizing the path of modular robots through a static grid of different terrain blocks. Each chromosome consists of path and modular robot configurations. Solution of the proposed algorithm is a proper path and configuration pattern for crossing the environment with minimum effort related to a pre-defined multi-objective function. Finally, for investigating the efficiency of the proposed algorithm, the performance of proposed algorithm is compared to Dijkstra algorithm in different environments.