A comparison of three uncertainty calculi for building sonar-based occupancy grids

Abstract In this paper, we describe and compare three different uncertainty calculi techniques to build occupancy grids of an unknown environment using sensory information provided by a ring of ultrasonic range-finders. These techniques are based on Bayesian theory, Dempster–Shafer theory of evidence, and fuzzy set theory. Several sensor models are presented to handle uncertainty according to the selected building procedure. Experimental examples of occupancy grids, built from real data recorded by two different mobile robots in office-like environment, are presented to perform a comparison among the proposed calculi techniques. Probabilistic and evidence theoretic methods are more accurate in structured environments, while in cases of multiple reflections only the possibilistic approach provides correct results.