Ultsch, Johannes and Brembeck, Jonathan and de Castro, Ricardo (2019) Learning-Based Path Following Control for an Over-Actuated Robotic Vehicle. In: 9th VDI / VDE symposium on Control technology for automated driving and networked mobility, AUTOREG 2019, 2349, pp. 25-46. VDI Verlag GmbH. AUTOREG 2019, 02.-03. Juli 2019, Mannheim, Deutschland. doi: 10.51202/9783181023495-25. ISBN 978-3-18-092349-9. ISSN 0083-5560.
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Abstract
Motion control, in particular path following control (PFC), is an important function of autonomous vehicles. PFC controls the propulsion, steering and braking such that the vehicle follows a parametric path and reference velocity. For the design of traditional model-based PFC approaches a sufficiently accurate synthesis model of the vehicle has to be available in order to design a performant controller. However, constructing, parametrizing and testing these model-based PFC as well as deriving the synthesis model is known to be a time-consuming task. Recently the application of reinforcement learning (RL) methods to solve control problems without a synthesis model but based on high fidelity simulation models has gained increasing interest. In this paper we investigate the application of RL methods to solve the path following problem for DLR’s ROboMObil, an over-actuated robotic vehicle. Simulation results demonstrate that the RL-based PFC exhibits similar tracking performance as a model-based controller, executed on the path used for training. Moreover the RL-based PFC provides encouraging generalization capabilities, when facing unseen reference paths.
Item URL in elib: | https://elib.dlr.de/127819/ | ||||||||||||
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Document Type: | Conference or Workshop Item (Speech) | ||||||||||||
Title: | Learning-Based Path Following Control for an Over-Actuated Robotic Vehicle | ||||||||||||
Authors: |
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Date: | 2019 | ||||||||||||
Journal or Publication Title: | 9th VDI / VDE symposium on Control technology for automated driving and networked mobility, AUTOREG 2019 | ||||||||||||
Refereed publication: | Yes | ||||||||||||
Open Access: | Yes | ||||||||||||
Gold Open Access: | No | ||||||||||||
In SCOPUS: | Yes | ||||||||||||
In ISI Web of Science: | No | ||||||||||||
Volume: | 2349 | ||||||||||||
DOI: | 10.51202/9783181023495-25 | ||||||||||||
Page Range: | pp. 25-46 | ||||||||||||
Editors: |
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Publisher: | VDI Verlag GmbH | ||||||||||||
Series Name: | VDI-Berichte | ||||||||||||
ISSN: | 0083-5560 | ||||||||||||
ISBN: | 978-3-18-092349-9 | ||||||||||||
Status: | Published | ||||||||||||
Keywords: | Reinforcement Learning, Pfadfolgeregelung | ||||||||||||
Event Title: | AUTOREG 2019 | ||||||||||||
Event Location: | Mannheim, Deutschland | ||||||||||||
Event Type: | national Conference | ||||||||||||
Event Dates: | 02.-03. Juli 2019 | ||||||||||||
Organizer: | VDI Wissensforum | ||||||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||
HGF - Program: | Space | ||||||||||||
HGF - Program Themes: | Space System Technology | ||||||||||||
DLR - Research area: | Raumfahrt | ||||||||||||
DLR - Program: | R SY - Space System Technology | ||||||||||||
DLR - Research theme (Project): | R - Vorhaben Intelligente Mobilität (old) | ||||||||||||
Location: | Oberpfaffenhofen | ||||||||||||
Institutes and Institutions: | Institute of System Dynamics and Control > Vehicle System Dynamics | ||||||||||||
Deposited By: | Ultsch, Johannes | ||||||||||||
Deposited On: | 12 Jul 2019 14:21 | ||||||||||||
Last Modified: | 10 Jan 2022 17:34 |
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