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Conference Papers Year : 2021

Combining Bayesian and AI approaches for Autonomous Driving

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Abstract

Invited Keynote Talk. This talk addresses the exciting new concept of Autonomous Driving, as well as the technical questions and solutions associated with it. Emphasis will be placed on the scientific and technological challenges associated with issues of embedded perception, understanding of complex dynamic scenes and real-time driving decision-making. It will be shown how these problems can be tackled using Bayesian Perception, Artificial Intelligence and Machine Learning approaches. The talk will be illustrated using results obtained by Inria Grenoble Rhône-Alpes (France) in the scope of several R&D projects conducted in collaboration with IRT Nanoelec (French Technological Research Institute) and with several industrial companies such as Toyota or Renault.
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Dates and versions

hal-03518232 , version 1 (09-01-2022)

Identifiers

  • HAL Id : hal-03518232 , version 1

Cite

Christian Laugier. Combining Bayesian and AI approaches for Autonomous Driving. IROS 2021 - IEEE/RSJ International Conference on Intelligent Robots and Systems - Workshop "Perception and Navigation for Autonomous Robotics in Unstructured and Dynamic Environments", Sep 2021, Prague, Czech Republic. ⟨hal-03518232⟩
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