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Conference Papers Year : 2021

Information-Theoretic Sensor-Based Predictive Control for Autonomous Vehicle Navigation: A Proof of Concept

Abstract

This paper explores the feasibility of an Information-Theoretic Sensor-Based Predictive Control (IT-SBPC) approach for autonomous navigation in presence of pedestrians. Our technique relies solely in sensor data expressed relative to the vehicle and therefore no localization is inherently required. By combining the advantages of the information-theoretic framework and sensor-based formalism, the proposed technique drives the vehicle safely and smoothly towards the desired goal. Several real-time simulated scenarios, showing that the car is able to reach the goal with centimeter-level accuracy, validate the effectiveness of our approach.
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Dates and versions

hal-03413632 , version 1 (09-02-2022)

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David Perez-Morales, Vincent Frémont. Information-Theoretic Sensor-Based Predictive Control for Autonomous Vehicle Navigation: A Proof of Concept. 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), Sep 2021, Indianapolis, United States. pp.879-884, ⟨10.1109/ITSC48978.2021.9564855⟩. ⟨hal-03413632⟩
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