An integrated approach for multilane robot motion planning using motor schema and fuzzy logic

This paper presents a novel multilane-based approach that integrates global and local path planning of mobile robots. It employs motor schema-based behavior coordination with fuzzy logic-based adaptive behavioral modulation. Voronoi diagram and A* search algorithm are exploited to determine the global safe-path and subgoals between the starting point of the robot and target. Safe lanes are formed around the safe-path. The robot locally optimizes the path length using a cost function for on-line selection of obstacle-free safe lane. Motor schema based behavior fusion is used for on-line coordination of force vectors originated from the subgoal, safe path and obstacles to generate the safe heading direction. A supervisory fuzzy module is developed to dynamically produce the force coefficients for context dependent modulation of the virtual forces. Adapted vector field histogram is deployed in order to modify the safe path in the presence of unknown obstacles. Simulation of navigation examples validates the performance of the algorithm.