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HMA-RRT: A hybrid multi-strategy adaptive RRT algorithm for USV path planning in complex maritime environments
by
Wang, Jiyun
, Jiang, Zhenpeng
, Wang, Yu
, Liu, Qingquan
, Wang, Ende
in
Adaptive algorithms
/ Artificial Potential Field (APF)
/ Autonomous navigation
/ Computer Imaging
/ Computer Science
/ Database Management
/ Efficiency
/ Energy consumption
/ Heuristic
/ Islands
/ Kinematics
/ Machine Learning
/ Multi-objective optimization
/ Multiple objective analysis
/ Obstacle avoidance
/ Ocean currents
/ Optimization algorithms
/ Original Paper
/ Path planning
/ Pattern Recognition and Graphics
/ Planning
/ Potential fields
/ RRT
/ Smoothness
/ Software Engineering/Programming and Operating Systems
/ Strategy
/ Surface vehicles
/ Systems and Data Security
/ Systems stability
/ Theory of Computation
/ Unmanned Surface Vehicle (USV)
/ Unmanned vehicles
/ Vision
/ Waterways
2026
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HMA-RRT: A hybrid multi-strategy adaptive RRT algorithm for USV path planning in complex maritime environments
by
Wang, Jiyun
, Jiang, Zhenpeng
, Wang, Yu
, Liu, Qingquan
, Wang, Ende
in
Adaptive algorithms
/ Artificial Potential Field (APF)
/ Autonomous navigation
/ Computer Imaging
/ Computer Science
/ Database Management
/ Efficiency
/ Energy consumption
/ Heuristic
/ Islands
/ Kinematics
/ Machine Learning
/ Multi-objective optimization
/ Multiple objective analysis
/ Obstacle avoidance
/ Ocean currents
/ Optimization algorithms
/ Original Paper
/ Path planning
/ Pattern Recognition and Graphics
/ Planning
/ Potential fields
/ RRT
/ Smoothness
/ Software Engineering/Programming and Operating Systems
/ Strategy
/ Surface vehicles
/ Systems and Data Security
/ Systems stability
/ Theory of Computation
/ Unmanned Surface Vehicle (USV)
/ Unmanned vehicles
/ Vision
/ Waterways
2026
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HMA-RRT: A hybrid multi-strategy adaptive RRT algorithm for USV path planning in complex maritime environments
by
Wang, Jiyun
, Jiang, Zhenpeng
, Wang, Yu
, Liu, Qingquan
, Wang, Ende
in
Adaptive algorithms
/ Artificial Potential Field (APF)
/ Autonomous navigation
/ Computer Imaging
/ Computer Science
/ Database Management
/ Efficiency
/ Energy consumption
/ Heuristic
/ Islands
/ Kinematics
/ Machine Learning
/ Multi-objective optimization
/ Multiple objective analysis
/ Obstacle avoidance
/ Ocean currents
/ Optimization algorithms
/ Original Paper
/ Path planning
/ Pattern Recognition and Graphics
/ Planning
/ Potential fields
/ RRT
/ Smoothness
/ Software Engineering/Programming and Operating Systems
/ Strategy
/ Surface vehicles
/ Systems and Data Security
/ Systems stability
/ Theory of Computation
/ Unmanned Surface Vehicle (USV)
/ Unmanned vehicles
/ Vision
/ Waterways
2026
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HMA-RRT: A hybrid multi-strategy adaptive RRT algorithm for USV path planning in complex maritime environments
Journal Article
HMA-RRT: A hybrid multi-strategy adaptive RRT algorithm for USV path planning in complex maritime environments
2026
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Overview
To address the global path planning challenge for Unmanned Surface Vehicles in complex maritime environments characterized by dense islands and narrow waterways, this paper proposes a Hybrid Multi-Strategy Adaptive RRT* algorithm. The method combines a dynamic region-based sampling strategy with an improved artificial potential field based dynamic extension strategy, which introduces random-node attraction, dynamic repulsion adjustments, and additional repulsive forces. Additionally, a hierarchical side-retreat escape mechanism is applied to enhance obstacle avoidance and search efficiency in complex environments. The algorithm also incorporates heading-angle constraints and adaptive step-size adjustment to ensure the path complies with USV kinematic properties. Furthermore, an improved NSGA-II algorithm is proposed to perform multi-objective optimization of path length, smoothness, and safety, and B-spline interpolation is used to generate continuous and executable paths. Simulation results show that, compared with the standard RRT* algorithm, the proposed HMA-RRT* algorithm achieves average reductions of 7.85% in path length, 66.96% in node count, 48.73% in computation time, and 25.7% in mean turning angle across four representative complex maritime environments. These improvements significantly enhance search efficiency, path smoothness, and planning feasibility, thereby providing a reliable and efficient path-planning solution for autonomous USV navigation in complex maritime conditions.
Graphical abstract
Publisher
Springer International Publishing,Springer Nature B.V,Springer
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