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MOMDP solving algorithms comparison for safe path planning problems in urban environments

Delamer, Jean-Alexis and Watanabe, Yoko and Ponzoni Carvalho Chanel, Caroline MOMDP solving algorithms comparison for safe path planning problems in urban environments. (2018) In: 10th Workshop on Planning, Perception and Navigation for Intelligent Vehicles, 1 October 2018 (Madrid, Spain).

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Official URL: https://project.inria.fr/ppniv18/files/2018/10/paper2.pdf

Abstract

This paper tackles a problem of UAV safe path planning in an urban environment where the onboard sensors can be unavailable such as GPS occlusion. The key idea is to perform UAV path planning along with its navigation an guidance mode planning where each of these modes uses different set of sensors and whose availability and performance are environment-dependent. It is supposed to have a-priori knowledge in a form of gaussians mixture maps of obstacles and sensors availabilities. These maps allow the use of an Extended Kalman Filter (EKF) to have an accurate state estimate. This paper proposes a planner model based on Mixed Observability Markov Decision Process (MOMDP) and EKF. It allows the planner to propagate such probability map information to the future path for choosing the best action minimizing the expected cost.

Item Type:Conference or Workshop Item (Paper)
HAL Id:hal-01974265
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
French research institutions > Office National d'Etudes et Recherches Aérospatiales - ONERA (FRANCE)
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Deposited By: Caroline Ponzoni Carvalho Chanel
Deposited On:08 Jan 2019 15:40

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