【摘要】 无人机技术在灾害救援、农业植保、物流配送、军事等领域得到了广泛应用,无人机路径规划作为无人机自主导航的核心技术,直接影响其任务执行效率、安全性和适应性。在传统人工势场法（APF）基础上,本文提出了势场模型增强引导、虚拟子目标机制及局部路径平滑,实现复杂场景下的无人机实时路径规划能力。以城市建筑为背景,实现了多建筑物复杂环境下的路径规划,与全局规划A~*算法对比,验证改进APF的适应性、路径规划效果及计算效率。更多还原

【Abstract】 Unmanned Aerial Vehicle(UAV) technology has been widely applied in various fields such as disaster relief,agricultural plant protection, logistics distribution,and military operations.As a core technology for UAV autonomous navigation, UAV path planning directly influences its mission execution efficiency,safety,and adaptability.Building upon the traditional Artificial Potential Field(APF) method,this paper proposes an enhanced guidance mechanism through improved potential field modeling,a virtual sub-goal mechanism,and local path smoothing to achieve real-time path planning capabilities for UAVs in complex scenarios.Taking urban buildings as the background, this study implements path planning in a multi-building complex environment.By comparing with the global A~*algorithm,the adaptability,path planning effectiveness,and computational efficiency of the improved APF are verified.更多还原