A Robot Path Planning Method Based on Synergy Behavior of Cockroach Colony

Abstract

By studying the biological behavior of cockroaches, a bionic algorithm, Cooperative Learning Cockroach Colony Optimization (CLCCO), is presented in this paper. The aim of CLCCO is to provide an efficient method to solve Robot Path Planning (RPP) problems. The CLCCO algorithm is based on the idea of synergy behavior of cockroach colony and machine learning. With pheromone, the cockroach colony achieves population synergy, which includes the follow and diversion behaviors. The strategy of Fibonacci transformation is used for the cockroach individual to choose the next feasible cell. The technologies of λ-geometry and multi-objective search make the paths searched smoother and greatly improve the algorithm search efficiency. In particular, the CLCCO algorithm requires only two parameters to be set. When CLCCO is applied to real robots, a path compression technique is designed. The simulation results show that the CLCCO algorithm demonstrates high efficiency in mostly tests.