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Path Planning Based on Ant Colony Algorithm and Distributed Local Navigation for Multi-Robot Systems

This paper presents a decoupled path planning based on ant colony algorithm and distributed navigation with collision avoidance for multi-robot systems. An improved ant colony algorithm is proposed to plan a reasonable collision-free path for each mobile robot of multi-robot system in the decoupled path planning scheme in complicated static environment. The special functions are added into the regular ant colony algorithm to improve the selective strategy. When an ant explores a dead-corner in path searching, a dead-corner table is established and a penalty function is used for the trail intensity updated in order to avoid the path deadlock of mobile robot. A behavior strategy on "first come and first service" is adopted to solve the conflict between moving robots in distributed local navigation. Simulation results show that the proposed method can effectively improve the performance of the planned path, and the individual robots with collision-free can achieve to reach their goal locations by the simple local navigation strategies