Real-Time Obstacle Avoidance for Car Robot Using Potential Field and Local Incremental Planning

Integration of local incremental planning and potential field is proposed for a motion planning of the car-like robot in this research so that obstacle avoidance and goal seeking could be achieved in real time. The feedback linearization control using a desired trajectory generated from the virtual force of potential function could help accomplishing these objectives. Both attractive and repulsive forces are function of both relative position and velocity between robot-obstacle and robot-target. The motion planning of the car-like robot has been demonstrated using this new local incremental planning when the unknown and dynamics environment contains either fixed multiple obstacles or moving obstacles. Results, demonstrated in Matlab simulation, reveal that the car-like robot can reach the target point and avoid moving obstacles at the same time, which could be implemented for a real car robot in near future.