Motion Planning Approach for Car-Like Robots in Unstructured Scenario.

When a car-like robot travels in an unstructured scenario, real-time motion planning encounters the problem of unstable motion state in obstacle avoidance planning. This paper presents a hybrid motion planning approach based on the timed-elastic-band (TEB) approach and artificial potential field. Different potential fields in an unstructured scenario are established, and the real-time velocity of the car-like robot is planned by using the conversion function of the virtual potential energy of the superimposed potential field and the virtual kinetic energy of the robot. The optimized TEB approach plans the local optimal path and solves the problems related to the local minimum region and non-reachable targets. The safety area of the dynamic obstacle is constructed to realize turning or emergency stop obstacle avoidance, thereby effectively ensuring the safety of the car-like robot in emergency situations. The simulation experiments show that the proposed approach has superior kinematic characteristics and satisfactory obstacle avoidance planning effects and can improve the motion comfort and safety of the car-like robot. In the practical test, the car-like robot moves stably in a dynamic scenario, and the proposed approach satisfies the actual application requirements.