Computing Occupancy Grids From Multiple Sensors Using Linear Opinion Pools

Perception is a key component for any robotic system. In this paper we present a method to construct occupancy grids by fusing sensory information using Linear Opinion Pools. We used lidar sensors and a stereo-vision system mounted on a vehicle to make the experiments. To perform the validation, we compared the proposed method with the fusion method previously used in the Bayesian Occupancy Filter framework, using real data taken from highway and urban scenarios. The results show that our method is better at dealing with conflicting information coming from the sensors. We propose an implementation on parallel hardware which allows real-time execution.