Multi-agent informed path planning using the probability hypothesis density
An Informed Path Planning algorithm for multiple agents is presented. It can be used to efficiently utilize available agents when surveying large areas, when total coverage is unattainable. Internally the algorithm has a Probability Hypothesis Density (PHD) representation, inspired by modern multi-t...
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ftnorce:oai:norceresearch.brage.unit.no:11250/2686928 2023-05-15T15:02:48+02:00 Multi-agent informed path planning using the probability hypothesis density Olofsson, Harald Lennart Jonatan Hendeby, Gustaf Lauknes, Tom Rune Johansen, Tor Arne 2020 application/pdf https://hdl.handle.net/11250/2686928 https://doi.org/10.1007/s10514-020-09904-1 eng eng Autonomous Robots. 2020, 44 913-925. urn:issn:0929-5593 https://hdl.handle.net/11250/2686928 https://doi.org/10.1007/s10514-020-09904-1 cristin:1820060 CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ © 2020, Authors CC-BY Autonomous Robots 44 913-925 Peer reviewed Journal article 2020 ftnorce https://doi.org/10.1007/s10514-020-09904-1 2022-10-13T05:50:26Z An Informed Path Planning algorithm for multiple agents is presented. It can be used to efficiently utilize available agents when surveying large areas, when total coverage is unattainable. Internally the algorithm has a Probability Hypothesis Density (PHD) representation, inspired by modern multi-target tracking methods, to represent unseen objects. Using the PHD, the expected number of observed objects is optimized. In a sequential manner, each agent maximizes the number of observed new targets, taking into account the probability of undetected objects due to previous agents’ actions and the probability of detection, which yields a scalable algorithm. Algorithm properties are evaluated in simulations, and shown to outperform a greedy base line method. The algorithm is also evaluated by applying it to a sea ice tracking problem, using two datasets collected in the Arctic, with reasonable results. An implementation is provided under an Open Source license. acceptedVersion Article in Journal/Newspaper Arctic Sea ice NORCE vitenarkiv (Norwegian Research Centre) Arctic Autonomous Robots 44 6 913 925 |
institution |
Open Polar |
collection |
NORCE vitenarkiv (Norwegian Research Centre) |
op_collection_id |
ftnorce |
language |
English |
description |
An Informed Path Planning algorithm for multiple agents is presented. It can be used to efficiently utilize available agents when surveying large areas, when total coverage is unattainable. Internally the algorithm has a Probability Hypothesis Density (PHD) representation, inspired by modern multi-target tracking methods, to represent unseen objects. Using the PHD, the expected number of observed objects is optimized. In a sequential manner, each agent maximizes the number of observed new targets, taking into account the probability of undetected objects due to previous agents’ actions and the probability of detection, which yields a scalable algorithm. Algorithm properties are evaluated in simulations, and shown to outperform a greedy base line method. The algorithm is also evaluated by applying it to a sea ice tracking problem, using two datasets collected in the Arctic, with reasonable results. An implementation is provided under an Open Source license. acceptedVersion |
format |
Article in Journal/Newspaper |
author |
Olofsson, Harald Lennart Jonatan Hendeby, Gustaf Lauknes, Tom Rune Johansen, Tor Arne |
spellingShingle |
Olofsson, Harald Lennart Jonatan Hendeby, Gustaf Lauknes, Tom Rune Johansen, Tor Arne Multi-agent informed path planning using the probability hypothesis density |
author_facet |
Olofsson, Harald Lennart Jonatan Hendeby, Gustaf Lauknes, Tom Rune Johansen, Tor Arne |
author_sort |
Olofsson, Harald Lennart Jonatan |
title |
Multi-agent informed path planning using the probability hypothesis density |
title_short |
Multi-agent informed path planning using the probability hypothesis density |
title_full |
Multi-agent informed path planning using the probability hypothesis density |
title_fullStr |
Multi-agent informed path planning using the probability hypothesis density |
title_full_unstemmed |
Multi-agent informed path planning using the probability hypothesis density |
title_sort |
multi-agent informed path planning using the probability hypothesis density |
publishDate |
2020 |
url |
https://hdl.handle.net/11250/2686928 https://doi.org/10.1007/s10514-020-09904-1 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
Autonomous Robots 44 913-925 |
op_relation |
Autonomous Robots. 2020, 44 913-925. urn:issn:0929-5593 https://hdl.handle.net/11250/2686928 https://doi.org/10.1007/s10514-020-09904-1 cristin:1820060 |
op_rights |
CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ © 2020, Authors |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1007/s10514-020-09904-1 |
container_title |
Autonomous Robots |
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44 |
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6 |
container_start_page |
913 |
op_container_end_page |
925 |
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1766334721414922240 |