Multi-Strategy Fusion Path Planning Algorithm for Autonomous Surface Vessels with Dynamic Obstacles
Considering the complexity and variability inherent in maritime environments, path planning algorithms for navigation have consistently been a subject of intense research interest. Nonetheless, single-algorithm approaches often exhibit inherent limitations. Consequently, this study introduces a path...
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Published in | Journal of marine science and engineering Vol. 13; no. 7; p. 1357 |
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Format | Journal Article |
Language | English |
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Abstract | Considering the complexity and variability inherent in maritime environments, path planning algorithms for navigation have consistently been a subject of intense research interest. Nonetheless, single-algorithm approaches often exhibit inherent limitations. Consequently, this study introduces a path planning algorithm for autonomous surface vessels (ASVs) that integrates an improved fast marching method (FMM) with the dynamic window approach (DWA) for underactuated ASVs. The enhanced FMM improves the overall optimality and safety of the determined path in comparison to the conventional approach. Concurrently, it effectively merges the local planning strengths of the DWA algorithm, addressing the safety re-planning needs of the global path when encountering dynamic obstacles, thus augmenting path tracking accuracy and navigational stability. The efficient hybrid algorithm yields notable improvements in the path planning success rate, obstacle avoidance efficacy, and path smoothness compared with the isolated employment of either FMM or DWA, demonstrating superiority and practical applicability in maritime scenarios. Through a comprehensive analysis of its control output, the proposed integrated algorithm accomplishes efficient obstacle avoidance via agile control of angular velocity while preserving navigational stability and achieves path optimization through consistent acceleration adjustments, thereby asserting its superiority and practical worth in challenging maritime environments. |
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AbstractList | Considering the complexity and variability inherent in maritime environments, path planning algorithms for navigation have consistently been a subject of intense research interest. Nonetheless, single-algorithm approaches often exhibit inherent limitations. Consequently, this study introduces a path planning algorithm for autonomous surface vessels (ASVs) that integrates an improved fast marching method (FMM) with the dynamic window approach (DWA) for underactuated ASVs. The enhanced FMM improves the overall optimality and safety of the determined path in comparison to the conventional approach. Concurrently, it effectively merges the local planning strengths of the DWA algorithm, addressing the safety re-planning needs of the global path when encountering dynamic obstacles, thus augmenting path tracking accuracy and navigational stability. The efficient hybrid algorithm yields notable improvements in the path planning success rate, obstacle avoidance efficacy, and path smoothness compared with the isolated employment of either FMM or DWA, demonstrating superiority and practical applicability in maritime scenarios. Through a comprehensive analysis of its control output, the proposed integrated algorithm accomplishes efficient obstacle avoidance via agile control of angular velocity while preserving navigational stability and achieves path optimization through consistent acceleration adjustments, thereby asserting its superiority and practical worth in challenging maritime environments. |
Audience | Academic |
Author | Liu, Chengyong Liu, Kang Xie, Yongshun He, Yixiong Ma, Yong |
Author_xml | – sequence: 1 givenname: Yongshun orcidid: 0009-0000-9837-6062 surname: Xie fullname: Xie, Yongshun – sequence: 2 givenname: Chengyong surname: Liu fullname: Liu, Chengyong – sequence: 3 givenname: Yixiong orcidid: 0000-0001-8960-2443 surname: He fullname: He, Yixiong – sequence: 4 givenname: Yong surname: Ma fullname: Ma, Yong – sequence: 5 givenname: Kang orcidid: 0000-0003-1657-0828 surname: Liu fullname: Liu, Kang |
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SubjectTerms | Algorithms Angular velocity autonomous surface vessels Efficiency fusion algorithm Local planning Methods Motion control Navigation Obstacle avoidance Optimization Path planning Path tracking Planning Smoothness Stability Surface craft underactuated kinematic model |
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Title | Multi-Strategy Fusion Path Planning Algorithm for Autonomous Surface Vessels with Dynamic Obstacles |
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