Occupancy Grid Mapping Based on DSmT for Dynamic Environment Perception

Abstract

Occupancy grid mapping is an important approach for intelligent vehicle environment perception. In this paper, an occupancy grid mapping approach in Dezert-Smarandache theory (DSmT) framework for the purpose of dynamic environment perception is proposed. To avoid the transformation of the local map from polar to Catersian coordinate, a different inverse sensor model in Cartesian coordinate for laser scanner was proposed. Two different combination rules in DSmT framework, Dempster’s rule of combination and PCR2, are implemented independently for global map update and mobile object detection. The performance of the two combination rules were compared by ways of simulation and experiment. According to the comparisons we find that both of the combination rules are capable of detecting mobile objects. And the former effectively filtered out the noise and make the detection robust, but the latter didn’t, suggesting that the former is more suitable for occupancy grid mapping. Static and mobile objects are extracted from the occupancy grid map using digital image processing technology.