Embedded Bayesian Perception by Dynamic Occupancy Grid Filtering

International audienceA generic Bayesian perception framework, designed to estimate a dense representation of dynamic environments, by fusing and filtering multi-sensor data, has been developed, implemented and tested on embedded devices. The main features of the approach are the followings:• Data from multiple sensors are properly fused in probabilistic occupancy grids.• Motion and robust occupancy are estimated by a specific Bayesian filter.• Short-term collision risks and object parameters are assessed.• The whole system has been implemented and tested on Nvidia embedded devices, and produces real-time results