Integrated motion planning for indoor mobile robots using motor schema and adaptive fuzzy behavioral modulation

This paper presents a novel approach for integrating global and local path planning of indoor mobile robots using motor schema based behavior coordination with fuzzy logic based adaptive behavioral modulation. First, Voronoi diagram approach is exploited to determine the global safe-path. Then A* search algorithm is employed to identify the Voronoi vertices (junctions or nodes) along the optimal path between the starting point of the robot and target position. Locally located junctions then act as subgoals for local motion planning. Motor schema based behavior fusion generates the safe direction of motion. Subgoals and points on the safe path exhibit attractive forces whereas obstacles cause repulsive forces. A supervisory fuzzy module is developed to incorporate adaptive behavioral capabilities which exploit the weighted decision-making based on contextual behavior composition. It dynamically produces the force coefficients for context dependent modulation of the virtual forces to generate local-minima free trajectory without oscillation. Adapted vector field histogram is deployed in order to modify the safe path in the presence of unknown obstacles. Simulation of indoor navigation examples validates the performance of the algorithm.