Motion Planning for Autonomous Vehicles in Partially Observable Environments

This work develops a motion planner that compensates the deficiencies from perception modules by exploiting the reaction capabilities of a vehicle. The work analyzes present uncertainties and defines driving objectives together with constraints that ensure safety. The resulting problem is solved in...

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Bibliographic Details
Main Author: Taş, Ömer Şahin (auth)
Format: Electronic Book Chapter
Language:English
Published: KIT Scientific Publishing 2023
Series:Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie
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Online Access:DOAB: download the publication
DOAB: description of the publication
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520 |a This work develops a motion planner that compensates the deficiencies from perception modules by exploiting the reaction capabilities of a vehicle. The work analyzes present uncertainties and defines driving objectives together with constraints that ensure safety. The resulting problem is solved in real-time, in two distinct ways: first, with nonlinear optimization, and secondly, by framing it as a partially observable Markov decision process and approximating the solution with sampling. 
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546 |a English 
650 7 |a Building construction & materials  |2 bicssc 
653 |a Robotics; Planning under Uncertainty; Decision Making; Information Gathering; Motion Planning; Robotik; Automatisiertes Fahren; Planung unter Unsicherheiten; Entscheidungsfindung; Bewegungsplanung 
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