Velocity obstacle approaches for multi-agent collision avoidance
This paper presents a critical analysis of some of the most promising approaches to geometric collision avoidance in multi-agent systems namely; the velocity obstacle (VO), reciprocal velocity obstacle (RVO), hybrid-reciprocal velocity obstacle (HRVO) and optimal reciprocal collision avoidance (ORCA...
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Language: | English |
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World Scientific Publishing
2019
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Online Access: | https://eprints.whiterose.ac.uk/141072/ https://eprints.whiterose.ac.uk/141072/1/Manuscript.pdf |
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ftleedsuniv:oai:eprints.whiterose.ac.uk:141072 2023-05-15T17:53:24+02:00 Velocity obstacle approaches for multi-agent collision avoidance Douthwaite, J. Zhao, S. Mihaylova, L.S. 2019-03-22 text https://eprints.whiterose.ac.uk/141072/ https://eprints.whiterose.ac.uk/141072/1/Manuscript.pdf en eng World Scientific Publishing https://eprints.whiterose.ac.uk/141072/1/Manuscript.pdf Douthwaite, J., Zhao, S. and Mihaylova, L.S. orcid.org/0000-0001-5856-2223 (2019) Velocity obstacle approaches for multi-agent collision avoidance. Unmanned Systems, 7 (1). pp. 55-64. ISSN 2301-3850 Article PeerReviewed 2019 ftleedsuniv 2023-01-30T22:14:53Z This paper presents a critical analysis of some of the most promising approaches to geometric collision avoidance in multi-agent systems namely; the velocity obstacle (VO), reciprocal velocity obstacle (RVO), hybrid-reciprocal velocity obstacle (HRVO) and optimal reciprocal collision avoidance (ORCA) approaches. Each approach is evaluated with respect to increasing agent populations and variable sensing assumptions. An intensive 1000 cycle Monte Carlo analysis is used to assess the performance of the selected algorithms in the presented conditions. The optimal reciprocal collision avoidance (ORCA) method is shown to yield the most scalable computation times and collision likelihood in different testing scenarios. The respective features and limitations of each algorithm are discussed and presented through examples. Article in Journal/Newspaper Orca White Rose Research Online (Universities of Leeds, Sheffield & York) Unmanned Systems 07 01 55 64 |
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Open Polar |
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White Rose Research Online (Universities of Leeds, Sheffield & York) |
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ftleedsuniv |
language |
English |
description |
This paper presents a critical analysis of some of the most promising approaches to geometric collision avoidance in multi-agent systems namely; the velocity obstacle (VO), reciprocal velocity obstacle (RVO), hybrid-reciprocal velocity obstacle (HRVO) and optimal reciprocal collision avoidance (ORCA) approaches. Each approach is evaluated with respect to increasing agent populations and variable sensing assumptions. An intensive 1000 cycle Monte Carlo analysis is used to assess the performance of the selected algorithms in the presented conditions. The optimal reciprocal collision avoidance (ORCA) method is shown to yield the most scalable computation times and collision likelihood in different testing scenarios. The respective features and limitations of each algorithm are discussed and presented through examples. |
format |
Article in Journal/Newspaper |
author |
Douthwaite, J. Zhao, S. Mihaylova, L.S. |
spellingShingle |
Douthwaite, J. Zhao, S. Mihaylova, L.S. Velocity obstacle approaches for multi-agent collision avoidance |
author_facet |
Douthwaite, J. Zhao, S. Mihaylova, L.S. |
author_sort |
Douthwaite, J. |
title |
Velocity obstacle approaches for multi-agent collision avoidance |
title_short |
Velocity obstacle approaches for multi-agent collision avoidance |
title_full |
Velocity obstacle approaches for multi-agent collision avoidance |
title_fullStr |
Velocity obstacle approaches for multi-agent collision avoidance |
title_full_unstemmed |
Velocity obstacle approaches for multi-agent collision avoidance |
title_sort |
velocity obstacle approaches for multi-agent collision avoidance |
publisher |
World Scientific Publishing |
publishDate |
2019 |
url |
https://eprints.whiterose.ac.uk/141072/ https://eprints.whiterose.ac.uk/141072/1/Manuscript.pdf |
genre |
Orca |
genre_facet |
Orca |
op_relation |
https://eprints.whiterose.ac.uk/141072/1/Manuscript.pdf Douthwaite, J., Zhao, S. and Mihaylova, L.S. orcid.org/0000-0001-5856-2223 (2019) Velocity obstacle approaches for multi-agent collision avoidance. Unmanned Systems, 7 (1). pp. 55-64. ISSN 2301-3850 |
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Unmanned Systems |
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07 |
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01 |
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55 |
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64 |
_version_ |
1766161120739983360 |