Cooperative Path Planning for Multiple Robots With Motion Constraints in Obstacle-Strewn Environment

A cooperative path searching approach is proposed to decouple cooperative path planning for multiple robots into the path planning phase and the trajectory tracking phase. Unexpected local environment changes or failures for some robots will not affect the regular running of other robots. The collision between robots and the motion constraints of robots are not considered in the first phase. A new connection point method suitable for the trap-like map is used to find the shortest path for every robot. Connection point method does not require much computation cost even if the grid map is zoomed in. In the second phase, a cooperative search tracking approach based on modified coevolution pigeon-inspired optimization algorithm is proposed to enable every robot to track the grid path obtained by the connection point method. A competition mechanism with serial number priority is used to cope with collisions between robots. The numerical simulations are performed to verify the effectiveness of the proposed approach.

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