Bayesian Perception & Decision for Autonomous Vehicles and Mobile Robots: From Research to Industrial Applications

Christian Laugier 1, 2
1 E-MOTION - Geometry and Probability for Motion and Action
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
2 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 : New technologies for Autonomous Vehicles and Mobile Robots are presented, with an emphasis on Multi-sensors Embedded Perception, Situation Awareness, Collision Risk Assessment, and Decision-making for safe navigation in Dynamic Human Environments. It is shown that Bayesian approaches are mandatory to develop such technologies and to obtain the required robustness in presence of uncertainty and of complex dynamic situations. It is also shown how the research results have been used to tackle some practical industrial problems.
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https://hal.inria.fr/hal-01436967
Contributor : Christian Laugier <>
Submitted on : Monday, January 16, 2017 - 7:05:32 PM
Last modification on : Friday, June 21, 2019 - 9:45:42 AM

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  • HAL Id : hal-01436967, version 1

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Christian Laugier. Bayesian Perception & Decision for Autonomous Vehicles and Mobile Robots: From Research to Industrial Applications. 2016. ⟨hal-01436967⟩

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