Local Minimum Free Motion Planning for Mobile Robots within Dynamic Environmetns

We build a local minimum free motion planning for mobile robots considering dynamic environments by simple sensor fusion assuming that there are unknown obstacles which can be detected only partially at a time by proximity sensors and can be cleaned up or moved slowly (dynamic environments). Potential field is used as a basic platform for the motion planning. To clear local minimum problem, the partial information on the obstacles should be memorized and integrated effectively. Sets of linked line segments (SLLS) are proposed as the integration method. Then robot's target point is replaced by virtual target considering the integrated sensing information. As for the main proximity sensors, we use laser slit emission and simple web camera since the system gives more continuous data information. Also, we use ultrasonic sensors as the auxiliary sensors for simple sensor fusion considering the advantages in that they give exact information about the presence of any obstacle within certain range. By using this sensor fusion, the dynamic environments can be dealt easily. The performance of our algorithm is validated via simulations and experiments.