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Beam Search Algorithm for Anti-Collision Trajectory Planning for Many-to-Many Encounter Situations with Autonomous Surface Vehicles

A single anti-collision trajectory generation problem for an “own” vessel only is significantly different from the challenge of generating a whole set of safe trajectories for multi-surface vehicle encounter situations in the open sea. Effective solutions for such problems are needed these days, as...

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Autores principales: Koszelew, Jolanta, Karbowska-Chilinska, Joanna, Ostrowski, Krzysztof, Kuczyński, Piotr, Kulbiej, Eric, Wołejsza, Piotr
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435611/
https://www.ncbi.nlm.nih.gov/pubmed/32722065
http://dx.doi.org/10.3390/s20154115
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author Koszelew, Jolanta
Karbowska-Chilinska, Joanna
Ostrowski, Krzysztof
Kuczyński, Piotr
Kulbiej, Eric
Wołejsza, Piotr
author_facet Koszelew, Jolanta
Karbowska-Chilinska, Joanna
Ostrowski, Krzysztof
Kuczyński, Piotr
Kulbiej, Eric
Wołejsza, Piotr
author_sort Koszelew, Jolanta
collection PubMed
description A single anti-collision trajectory generation problem for an “own” vessel only is significantly different from the challenge of generating a whole set of safe trajectories for multi-surface vehicle encounter situations in the open sea. Effective solutions for such problems are needed these days, as we are entering the era of autonomous ships. The article specifies the problem of anti-collision trajectory planning in many-to-many encounter situations. The proposed original multi-surface vehicle beam search algorithm (MBSA), based on the beam search strategy, solves the problem. The general idea of the MBSA involves the application of a solution for one-to-many encounter situations (using the beam search algorithm, BSA), which was tested on real automated radar plotting aid (ARPA) and automatic identification system (AIS) data. The test results for the MBSA were from simulated data, which are discussed in the final part. The article specifies the problem of anti-collision trajectory planning in many-to-many encounter situations involving moving autonomous surface vehicles, excluding Collision Regulations (COLREGs) and vehicle dynamics.
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spelling pubmed-74356112020-08-28 Beam Search Algorithm for Anti-Collision Trajectory Planning for Many-to-Many Encounter Situations with Autonomous Surface Vehicles Koszelew, Jolanta Karbowska-Chilinska, Joanna Ostrowski, Krzysztof Kuczyński, Piotr Kulbiej, Eric Wołejsza, Piotr Sensors (Basel) Article A single anti-collision trajectory generation problem for an “own” vessel only is significantly different from the challenge of generating a whole set of safe trajectories for multi-surface vehicle encounter situations in the open sea. Effective solutions for such problems are needed these days, as we are entering the era of autonomous ships. The article specifies the problem of anti-collision trajectory planning in many-to-many encounter situations. The proposed original multi-surface vehicle beam search algorithm (MBSA), based on the beam search strategy, solves the problem. The general idea of the MBSA involves the application of a solution for one-to-many encounter situations (using the beam search algorithm, BSA), which was tested on real automated radar plotting aid (ARPA) and automatic identification system (AIS) data. The test results for the MBSA were from simulated data, which are discussed in the final part. The article specifies the problem of anti-collision trajectory planning in many-to-many encounter situations involving moving autonomous surface vehicles, excluding Collision Regulations (COLREGs) and vehicle dynamics. MDPI 2020-07-24 /pmc/articles/PMC7435611/ /pubmed/32722065 http://dx.doi.org/10.3390/s20154115 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Koszelew, Jolanta
Karbowska-Chilinska, Joanna
Ostrowski, Krzysztof
Kuczyński, Piotr
Kulbiej, Eric
Wołejsza, Piotr
Beam Search Algorithm for Anti-Collision Trajectory Planning for Many-to-Many Encounter Situations with Autonomous Surface Vehicles
title Beam Search Algorithm for Anti-Collision Trajectory Planning for Many-to-Many Encounter Situations with Autonomous Surface Vehicles
title_full Beam Search Algorithm for Anti-Collision Trajectory Planning for Many-to-Many Encounter Situations with Autonomous Surface Vehicles
title_fullStr Beam Search Algorithm for Anti-Collision Trajectory Planning for Many-to-Many Encounter Situations with Autonomous Surface Vehicles
title_full_unstemmed Beam Search Algorithm for Anti-Collision Trajectory Planning for Many-to-Many Encounter Situations with Autonomous Surface Vehicles
title_short Beam Search Algorithm for Anti-Collision Trajectory Planning for Many-to-Many Encounter Situations with Autonomous Surface Vehicles
title_sort beam search algorithm for anti-collision trajectory planning for many-to-many encounter situations with autonomous surface vehicles
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435611/
https://www.ncbi.nlm.nih.gov/pubmed/32722065
http://dx.doi.org/10.3390/s20154115
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