基于A-Star和DWA算法的野外环境路径规划

doi:10.1007/s12204-024-2731-2

摘要/Abstract

摘要： 多要素复杂野外环境的路径规划问题仍然是一个挑战。设计了一种将全局规划和局部规划相结合的算法，应用于野外环境路径规划。提出了野外环境地图的建模过程。设计了三种优化策略来克服接触障碍物边缘、冗余节点和扭曲路径等问题，以提高A-Star算法性能，并设计了一种新的加权成本函数来实现不同的规划模式。此外，与传统的动态窗口方法（DWA）相比，改进的DWA避免了局部最优，提高了时间效率。为了对野外环境进行必要的路径重规划，将改进的A-Star与改进的DWA相结合，实现了野外环境中存在未知障碍物和移动障碍物的多要素重规划。改进的融合算法有效地解决了上述问题，节省了时间，仿真结果验证了改进算法的有效性。

关键词: 路径规划，路径重规划，野外环境，A-Star算法，DWA算法

Abstract: The path planning problem of complex wild environment with multiple elements still poses challenges. This paper designs an algorithm that integrates global and local planning to apply to the wild environmental path planning. The modeling process of wild environment map is designed. Three optimization strategies are designed to improve the A-Star in overcoming the problems of touching the edge of obstacles, redundant nodes and twisting paths. A new weighted cost function is designed to achieve different planning modes. Furthermore, the improved dynamic window approach (DWA) is designed to avoid local optimality and improve time efficiency compare to traditional DWA. For the necessary path re-planning of wild environment, the improved A-Star is integrated with the improved DWA to solve re-planning problem of unknown and moving obstacles in wild environment with multiple elements. The improved fusion algorithm effectively solves problems and consumes less time, and the simulation results verify the effectiveness of improved algorithms above.

Key words: path planning, path re-planning, wild environment, A-Star algorithm, dynamic window approach(DWA)

中图分类号:

TP242

董德金1,2，董诗音3，章露露1,2，蔡云泽1,2. 基于A-Star和DWA算法的野外环境路径规划[J]. J Shanghai Jiaotong Univ Sci, 2024, 29(4): 725-736.

DONG Dejin^1,2 (董德金), DONG Shiyin³ (董诗音), ZHANG Lulu^1,2 (章露露), CAI Yunze^1,2∗ (蔡云泽). Multi-AGVs Scheduling with Vehicle Conflict Consideration in Ship Outfitting Items Warehouse[J]. J Shanghai Jiaotong Univ Sci, 2024, 29(4): 725-736.

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