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Improved Dynamic Window Approach for Unmanned Surface Vehicles’ Local Path Planning Considering the Impact of Environmental Factors

The aim of local path planning for unmanned surface vehicles (USVs) is to avoid unknown dynamic or static obstacles. However, current relative studies have not fully considered the impact of ocean environmental factors which significantly increase the control difficulty and collision risk of USVs. T...

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Autores principales: Wang, Zhenyu, Liang, Yan, Gong, Changwei, Zhou, Yichang, Zeng, Cen, Zhu, Songli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321648/
https://www.ncbi.nlm.nih.gov/pubmed/35890861
http://dx.doi.org/10.3390/s22145181
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author Wang, Zhenyu
Liang, Yan
Gong, Changwei
Zhou, Yichang
Zeng, Cen
Zhu, Songli
author_facet Wang, Zhenyu
Liang, Yan
Gong, Changwei
Zhou, Yichang
Zeng, Cen
Zhu, Songli
author_sort Wang, Zhenyu
collection PubMed
description The aim of local path planning for unmanned surface vehicles (USVs) is to avoid unknown dynamic or static obstacles. However, current relative studies have not fully considered the impact of ocean environmental factors which significantly increase the control difficulty and collision risk of USVs. Therefore, this work studies two ocean environmental factors, namely, wave and current, given that they both have a significant impact on USVs. Furthermore, we redesign a kinematic model of an USV and the evaluation function of a classical and practical local path planning method based on the dynamic window approach (DWA). As shown by the results of the simulations, the path length was impacted mainly by the intensity of the environmental load and slightly by the direction of the environmental load, but the navigation time was significantly influenced by both. Taking the situation in still water as a benchmark in terms of the intensity and direction of the environmental factors, the maximum change rates of the path length were 8.6% and 0.6%, respectively, but the maximum change rates of the navigating time were 17.9% and 25.6%, separately. In addition, the average calculation time of each cycle was only 0.0418 s, and the longest time did not exceed the simulation time corresponding to a single cycle of 0.1 s. This method has proven to be a good candidate for real-time local path planning of USVs since it systematically considers the impact of waves and currents on the navigation of USVs, and thus ensures that USVs can adjust to the planned path in time and avoid obstacles when navigating in the real ocean environment.
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spelling pubmed-93216482022-07-27 Improved Dynamic Window Approach for Unmanned Surface Vehicles’ Local Path Planning Considering the Impact of Environmental Factors Wang, Zhenyu Liang, Yan Gong, Changwei Zhou, Yichang Zeng, Cen Zhu, Songli Sensors (Basel) Article The aim of local path planning for unmanned surface vehicles (USVs) is to avoid unknown dynamic or static obstacles. However, current relative studies have not fully considered the impact of ocean environmental factors which significantly increase the control difficulty and collision risk of USVs. Therefore, this work studies two ocean environmental factors, namely, wave and current, given that they both have a significant impact on USVs. Furthermore, we redesign a kinematic model of an USV and the evaluation function of a classical and practical local path planning method based on the dynamic window approach (DWA). As shown by the results of the simulations, the path length was impacted mainly by the intensity of the environmental load and slightly by the direction of the environmental load, but the navigation time was significantly influenced by both. Taking the situation in still water as a benchmark in terms of the intensity and direction of the environmental factors, the maximum change rates of the path length were 8.6% and 0.6%, respectively, but the maximum change rates of the navigating time were 17.9% and 25.6%, separately. In addition, the average calculation time of each cycle was only 0.0418 s, and the longest time did not exceed the simulation time corresponding to a single cycle of 0.1 s. This method has proven to be a good candidate for real-time local path planning of USVs since it systematically considers the impact of waves and currents on the navigation of USVs, and thus ensures that USVs can adjust to the planned path in time and avoid obstacles when navigating in the real ocean environment. MDPI 2022-07-11 /pmc/articles/PMC9321648/ /pubmed/35890861 http://dx.doi.org/10.3390/s22145181 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Zhenyu
Liang, Yan
Gong, Changwei
Zhou, Yichang
Zeng, Cen
Zhu, Songli
Improved Dynamic Window Approach for Unmanned Surface Vehicles’ Local Path Planning Considering the Impact of Environmental Factors
title Improved Dynamic Window Approach for Unmanned Surface Vehicles’ Local Path Planning Considering the Impact of Environmental Factors
title_full Improved Dynamic Window Approach for Unmanned Surface Vehicles’ Local Path Planning Considering the Impact of Environmental Factors
title_fullStr Improved Dynamic Window Approach for Unmanned Surface Vehicles’ Local Path Planning Considering the Impact of Environmental Factors
title_full_unstemmed Improved Dynamic Window Approach for Unmanned Surface Vehicles’ Local Path Planning Considering the Impact of Environmental Factors
title_short Improved Dynamic Window Approach for Unmanned Surface Vehicles’ Local Path Planning Considering the Impact of Environmental Factors
title_sort improved dynamic window approach for unmanned surface vehicles’ local path planning considering the impact of environmental factors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321648/
https://www.ncbi.nlm.nih.gov/pubmed/35890861
http://dx.doi.org/10.3390/s22145181
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