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Embedded Bayesian Perception by Dynamic Occupancy Grid Filtering

Lukas Rummelhard 1 Christian Laugier 1 
1 CHROMA - Robots coopératifs et adaptés à la présence humaine en environnements dynamiques
Inria Grenoble - Rhône-Alpes, CITI - CITI Centre of Innovation in Telecommunications and Integration of services
Abstract : A 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.
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Submitted on : Saturday, December 23, 2017 - 8:15:13 PM
Last modification on : Monday, May 16, 2022 - 4:46:03 PM


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  • HAL Id : hal-01672134, version 1



Lukas Rummelhard, Christian Laugier. Embedded Bayesian Perception by Dynamic Occupancy Grid Filtering. GTC 2017 - GPU Technology Conference, May 2017, San Jose, California, United States. , pp.1, 2017. ⟨hal-01672134⟩



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