Event-Potential Method for Mobile Robot Motion Planning and Control

Motion planning and control of mobile robots is a challenging but crucial task for autonomous navigation. Since the actual environment is usually highly dynamic and has extremely high uncertainty and unpredictability, motion planning and control methods need to handle unexpected events and uncertainties in the environment, such as dynamic obstacles. Existing motion planning and control methods are usually decoupled processes. When unexpected events occur, the planner replans a new feasible plan based on new sensory information, and then the controller executes the new plan. Existing methods usually perform the perception, replanning, and control loop in real time. Replanning is an inefficient and time-consuming process since the robot needs to process new perception information and restart the planner. Also, the plan is not fully executed before the next loop which wastes most of the plan. We tackle this problem by introducing an event-potential method: a novel event-based potential field motion planning and control method that introduces event reference instead of time reference, which can locally modify the preplanned velocity along the trajectory using the resultant force generated by the attractive force from a trajectory and repulsive force from obstacles for obstacle avoidance. After completing obstacle avoidance, the event reference allows the robot to continue to track the original trajectory without replanning. We test and compare the eventpotential method with existing methods on a three-wheeled omnidirectional mobile robot. The framework can also be adapted to different robots and tasks.