Rohou, S., Jaulin, L., Mihaylova, L.S. orcid.org/0000-0001-5856-2223 et al. (2 more authors) (2017) Guaranteed computation of robot trajectories. Robotics and Autonomous Systems, 93. pp. 76-84. ISSN 0921-8890
Abstract
This paper proposes a new method for guaranteed integration of state equations. Within this framework, the variables of interest are trajectories submitted to both arithmetic and differential equations. The approach consists in formalizing a problem thanks to a constraint network and then apply these constraints to sets of trajectories. The contribution of the paper is to provide a reliable framework to enclose the solutions of these differential equations. Its use is shown to be simple, more general and more competitive than existing approaches dealing with guaranteed integration, especially when applied to mobile robotics. The flexibility of the developed framework allows to deal with non-linear differential equations or even differential inclusions built from datasets, while considering observations of the states of interest. An illustration of this method is given over several examples with mobile robots.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 Elsevier. This is an author produced version of a paper subsequently published in Robotics and Autonomous Systems. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
Keywords: | guaranteed integration; tube programming; mobile robotics; constraints; contractors; ODE |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 06 Apr 2017 11:22 |
Last Modified: | 27 Jul 2023 08:23 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.robot.2017.03.020 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:114446 |