Sensor-based motion planning for car-like mobile robots in unknown environments

This work deals with the sensor-based motion planning problem for car-like robots. Sensor-based versions of Lazy DRM and Lazy LRM are used to exploit the information obtained from sensors and to compute a feasible collision-free path. The algorithm tries to reach the goal, executing the local method in the known free region. If it succeeds, a path to the goal is found and the algorithm finishes. Otherwise, the algorithm executes more scans to extend its free space, an so on. We have performed some simulations that show the promise of our approach.