A two-phase navigation system for mobile robots in dynamic environments

This paper presents an implemented navigation system for mobile robots in dynamic environments. In order to take advantage of existing knowledge of the world and to deal with unknown obstacles in real time, our system divides motion planning into global path planning and local reactive navigation. The former uses genetic algorithm methods to find a collision-free path; the latter is implemented using neural network techniques to track the path generated by the global planner while avoiding unknown obstacles on the way. As a result, the system can adapt to dynamic environmental changes. Our experiments, both in simulation and on a real robot, showed that the system can find a reasonably good free path in a fraction of the time necessary to find an optimal free path, and it can effectively achieve its goal configurations without collision