An evidential approach to probabilistic map-building

Examines the problem of constructing and maintaining a map of of an autonomous vehicle´s environment for the purpose of navigation, using evidential reasoning. The inherent uncertainty in the origin of measurements of sensors demands a probabilistic approach to processing, or fusing, the new sensory information to build an accurate map. In this paper, the map is based on a two-dimensional occupancy grid. The sensor readings are `fused´ into the map using the Dempster-Shafer inference rule. This evidential approach with its multi-valued hypotheses allows quantitative analysis of the quality of the data. The map building system is experimentally evaluated using sonar data from real environments