Hybrid Path Planning Method for USV Based on Improved A-Star and DWA

Abstract

This paper presents a hybrid path planning method that integrates an enhanced A-Star algorithm with the Dynamic Window Approach (DWA). The proposed approach addresses the limitations of conventional A-Star algorithms in global path planning, particularly their inability to adaptively avoid obstacles in real-time. To improve navigation safety, the A-Star search strategy is enhanced by avoiding paths that intersect with obstacle vertices or pass through narrow channels. Additionally, a node optimization technique is introduced to remove redundant nodes by checking for collinearity in consecutive nodes. This optimization reduces the path length and ensures that the path maintains a safe distance from obstacles using parallel lines. An advanced Bézier curve smoothing method is also proposed, which adaptively selects control points to improve path smoothness and driving stability. By incorporating these improvements, the enhanced A-Star algorithm is combined with DWA to facilitate dynamic obstacle avoidance while generating global paths. The method accounts for the kinematic characteristics of the USV, as well as physical constraints such as linear and angular velocities, enabling effective handling of obstacles in dynamic environments and ensuring safe navigation. Simulation results demonstrate that the proposed algorithm generates secure global paths, significantly optimizing node count, path length, and smoothness, while effectively avoiding dynamic obstacles, thus ensuring safe navigation of the USV.

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