Path planning for unmanned surface vehicle in complex dynamic environment based on improved RRT*-Smart

Aiming at the path planning problem of unmanned surface vehicle (USV) in complex dynamic environment with moving multi-obstacle ships, a path planning method based on improved RRT*-Smart (RTSNew) was designed.Firstly, the sampling mode of nodes was optimized, nodes were sampled in the polar coordina...

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Main Authors: Lu DONG, Ailing XIONG
Format: Article
Language:zho
Published: POSTS&TELECOM PRESS Co., LTD 2022-06-01
Series:智能科学与技术学报
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Online Access:http://www.cjist.com.cn/thesisDetails#10.11959/j.issn.2096-6652.202229
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author Lu DONG
Ailing XIONG
author_facet Lu DONG
Ailing XIONG
author_sort Lu DONG
collection DOAJ
description Aiming at the path planning problem of unmanned surface vehicle (USV) in complex dynamic environment with moving multi-obstacle ships, a path planning method based on improved RRT*-Smart (RTSNew) was designed.Firstly, the sampling mode of nodes was optimized, nodes were sampled in the polar coordinate system with USV as the origin, an elliptical sampling range constraint was adopted to avoid invalid sampling, and a historical path buffer pool was used to make full use of the historical path.The optimization greatly reduced the amount of calculation and improved the speed of path planning.Secondly, the expansion mode of nodes was improved.In order to avoid treating dynamic obstacles as static obstacles, time information was added to each node to realize dynamic collision detection and the full use of dynamic obstacles motion information greatly improves the feasibility of the planned path.At the same time, considering the maneuverability of USV, the angle constraint was added in expansion of nodes to ensure smooth path.Finally, virtual obstacles were designed to mobile obstacle ships to make the planned path comply with International Regulations for Preventing Collisions at Sea (COLREGS).Based on VREP platform, the USV navigation simulation experiments and comparative experiments were carried out.The results show that RTSNew can make USV reach the destination efficiently and safely, and it performs better in planning efficiency, path optimization and path security than traditional methods in complex dynamic environment with multi-obstacle ships.RTSNew ensures that the motion path complies with COLREGS, and solves the problems of traditional methods: treating the dynamic obstacles as static obstacles, ignoring COLREGS, large amount of calculation and low efficiency, not suitable for the complex dynamic environment with moving multi-obstacle ships.
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institution Kabale University
issn 2096-6652
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publisher POSTS&TELECOM PRESS Co., LTD
record_format Article
series 智能科学与技术学报
spelling doaj-art-254541cbbaef438e90771b38c98feb622024-11-11T06:53:14ZzhoPOSTS&TELECOM PRESS Co., LTD智能科学与技术学报2096-66522022-06-01426427659640893Path planning for unmanned surface vehicle in complex dynamic environment based on improved RRT*-SmartLu DONGAiling XIONGAiming at the path planning problem of unmanned surface vehicle (USV) in complex dynamic environment with moving multi-obstacle ships, a path planning method based on improved RRT*-Smart (RTSNew) was designed.Firstly, the sampling mode of nodes was optimized, nodes were sampled in the polar coordinate system with USV as the origin, an elliptical sampling range constraint was adopted to avoid invalid sampling, and a historical path buffer pool was used to make full use of the historical path.The optimization greatly reduced the amount of calculation and improved the speed of path planning.Secondly, the expansion mode of nodes was improved.In order to avoid treating dynamic obstacles as static obstacles, time information was added to each node to realize dynamic collision detection and the full use of dynamic obstacles motion information greatly improves the feasibility of the planned path.At the same time, considering the maneuverability of USV, the angle constraint was added in expansion of nodes to ensure smooth path.Finally, virtual obstacles were designed to mobile obstacle ships to make the planned path comply with International Regulations for Preventing Collisions at Sea (COLREGS).Based on VREP platform, the USV navigation simulation experiments and comparative experiments were carried out.The results show that RTSNew can make USV reach the destination efficiently and safely, and it performs better in planning efficiency, path optimization and path security than traditional methods in complex dynamic environment with multi-obstacle ships.RTSNew ensures that the motion path complies with COLREGS, and solves the problems of traditional methods: treating the dynamic obstacles as static obstacles, ignoring COLREGS, large amount of calculation and low efficiency, not suitable for the complex dynamic environment with moving multi-obstacle ships.http://www.cjist.com.cn/thesisDetails#10.11959/j.issn.2096-6652.202229unmanned surface vehicle;RRT*-Smart;path planning;dynamic collision detection;COLREGS
spellingShingle Lu DONG
Ailing XIONG
Path planning for unmanned surface vehicle in complex dynamic environment based on improved RRT*-Smart
智能科学与技术学报
unmanned surface vehicle;RRT*-Smart;path planning;dynamic collision detection;COLREGS
title Path planning for unmanned surface vehicle in complex dynamic environment based on improved RRT*-Smart
title_full Path planning for unmanned surface vehicle in complex dynamic environment based on improved RRT*-Smart
title_fullStr Path planning for unmanned surface vehicle in complex dynamic environment based on improved RRT*-Smart
title_full_unstemmed Path planning for unmanned surface vehicle in complex dynamic environment based on improved RRT*-Smart
title_short Path planning for unmanned surface vehicle in complex dynamic environment based on improved RRT*-Smart
title_sort path planning for unmanned surface vehicle in complex dynamic environment based on improved rrt smart
topic unmanned surface vehicle;RRT*-Smart;path planning;dynamic collision detection;COLREGS
url http://www.cjist.com.cn/thesisDetails#10.11959/j.issn.2096-6652.202229
work_keys_str_mv AT ludong pathplanningforunmannedsurfacevehicleincomplexdynamicenvironmentbasedonimprovedrrtsmart
AT ailingxiong pathplanningforunmannedsurfacevehicleincomplexdynamicenvironmentbasedonimprovedrrtsmart