Adaptive Autonomous Navigation using Reactive Multi-agent System for Control Law Merging

International audience This paper deals with intelligent autonomous navigation of a vehicle in cluttered environment. We present a control architecture for safe and smooth navigation of a Unmanned Ground Vehicles (UGV). This control architecture is designed to allow the use of a single control law f...

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Bibliographic Details
Published in:Procedia Computer Science
Main Authors: Dafflon, Baudouin, Vilca, Jose, Gechter, Franck, Adouane, Lounis
Other Authors: Décision et Information pour les Systèmes de Production (DISP), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université Lumière - Lyon 2 (UL2), Laboratoire Systèmes et Transports (IRTES - SET), Université de Technologie de Belfort-Montbeliard (UTBM)-Institut de Recherche sur les Transports, l'Energie et la Société - IRTES, Institut Pascal (IP), SIGMA Clermont (SIGMA Clermont)-Université Clermont Auvergne 2017-2020 (UCA 2017-2020 )-Centre National de la Recherche Scientifique (CNRS), Koziel, S and Leifsson, L and Lees, M and Krzhizhanovskaya, VV and Dongarra, J and Sloot, PMA
Format: Conference Object
Language:English
Published: HAL CCSD 2015
Subjects:
Online Access:https://hal.archives-ouvertes.fr/hal-01575898
https://hal.archives-ouvertes.fr/hal-01575898/document
https://hal.archives-ouvertes.fr/hal-01575898/file/2015_Dafflon_PCS.pdf
https://doi.org/10.1016/j.procs.2015.05.262
Description
Summary:International audience This paper deals with intelligent autonomous navigation of a vehicle in cluttered environment. We present a control architecture for safe and smooth navigation of a Unmanned Ground Vehicles (UGV). This control architecture is designed to allow the use of a single control law for different vehicle contexts (attraction to the target, obstacle avoidance, etc.) [4]. The reactive obstacle avoidance strategy is based on the limit-cycle approach [2]. To manage the interaction between the controllers according to the context, the multi-agent system is proposed. Multi-agent systems are an efficient approach for problem solving and decision making. They can be applied to a wide range of applications thanks to their intrinsic properties such as self-organization/emergent phenomena. Merging approach between control laws is based on their properties to adapt the control to the environment. Different simulations on cluttered environments show the performance and the efficiency of our proposal, to obtain fully reactive and safe control strategy, for the navigation of a UGV.