Local action planning for mobile robot collision avoidance

This paper presents an approach to collision avoidance for mobile robots that uses local path planning within a map built from the robot's latest range measurements followed by a search for control commands to steer the robot towards the goal safely and efficiently. While the search for control commands allows robot dynamics to be taken into account and therefore allows for very smooth navigation behavior, planning is able to determine the optimal path towards the goal and minimizes the likelihood that the robot gets trapped in dead end situations. We introduce and compare several approaches to utilize the results of path planning in the search for good control commands. In extensive experiments, we show that our combined approach outperforms a collision avoidance that is purely based on local planning and we empirically investigate the pros-and-cons of the different search strategies for control commands and find one to significantly outperform the others.