关键词: 复杂环境决策优化, 低空物流配送, 改进A*算法, 动态权重优化, 三维向量叉积, 无人机

Abstract: To address the efficiency and safety challenges of UAVs in low-altitude logistics distribution within urban complex building clusters, an improved A* algorithm is proposed. First, the heuristic function is refined to resolve the inefficiency caused by redundant node searches in traditional A* algorithms. The three-dimensional vector cross product is introduced to eliminate decision-making uncertainties during the search process, thereby constraining the expansion scope of neighboring nodes. Second, the cost function is optimized by dynamically adjusting the heuristic weight coefficient based on the relative distance between nodes and the target, achieving a balance between search speed and path quality for safe and efficient planning. The algorithm is validated through grid-based 3D map simulations, demonstrating a 57.40% reduction in runtime, a 54.75% decrease in traversed grid nodes, and a 78.16% decline in path inflection points compared to the traditional A* algorithm. Furthermore, a UAV control platform is implemented using the ROS (robot operating system), and real-world experiments confirm the enhanced accuracy and operational efficiency of the improved algorithm in practical applications.

Key words: complex environment decision optimization, low-altitude logistics delivery, improved A* algorithm, dynamic weight optimization, three-dimensional vector cross product, unmanned aerial vehicle (UAV)