Real-time obstacle avoidance based on sensory information

Detecting unexpected obstacles and avoiding collisions is an important task for any autonomous mobile robot. In this paper we describe an approach using a sonar-based system that we have used in our indoor autonomous mobile system. The logical design of this system is shown, followed by a description of how it builds a knowledge of the environment. The information collected of the environment can be used for many applications like real-time obstacle avoidance, environment learning, position estimation. This method builds up two kind of maps: a occupancy grid which contains the probability value of each cell to be occupied and a orientation map which contains the expected orientation of the surface of each cell in the occupancy grid. Methods for filtering raw sensor data before using it for map generation together with experimental results are shown.