Obstacle Forbidden Zone Based Multi-robot Motion Planning in Unknown Environments

This paper proposes an obstacle forbidden zone based motion planning approach for multiple robots in unknown environments. In order to avoid possible collisions, the concept of forbidden zone is introduced, and the recurrent least square algorithm with restricted scale is adopted to anticipate the motions of other robots. After eliminating those candidate directions that are blocked by static and dynamic predictive obstacle forbidden zones successively, all collision-free directions are obtained and the suitable one is chosen with the consideration of goal information. The rationality of the proposed approach has been validated by simulations.