An Evolutionary-Cooperative Model Based on Cellular Automata and Genetic Algorithms for the Navigation of Robots Under Formation Control

Abstract

Formation control is the task of coordinating a group of robots to get into and to maintain a formation with a specific shape while moving in the environment. In this work we investigated models based on cellular automata applied to this task. We implemented methods previously described in the literature and found some limitations. Thus, an evolutionary-cooperative method is proposed, using the search power of a genetic algorithm along with the compact rules and simplified processing of cellular automata. The proposal required low computational infrastructure and was tested in a robotics simulator (Webots) with a team of 3 e-puck robots. The new model exhibited a better behaviour than their precursors in several scenarios, improving the robot's trajectory and formation maintenance.