空地协同作业场景下无人机快速路径规划与自主降落技术  

Rapid Path Planning and Autonomous Landing Technology ofUAVs in Air-Ground Collaborative Operation Scenarios

作　　者：曹宇辉 解明扬 李嘉铭 张民[1] 王从庆[1] CAO Yuhui;XIE Mingyang;LI Jiaming;ZHANG Min;WANG Congqing(College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211000,China)

机构地区：[1]南京航空航天大学自动化学院,南京211000

出　　处：《电光与控制》2023年第10期1-6,共6页Electronics Optics & Control

基　　金：国家自然科学基金青年基金(62003160);中央高校基本科研业务费(NT2022007);澳门青年学者计划项目(AM2020007)。

摘　　要：空地协同作业场景中要求无人机同时具备快速路径规划与精准自主降落功能,这对无人机搭载有限计算资源下算法的实时性和准确性提出了更高要求。主要解决了无人机快速路径规划与自主降落功能一体化实现关键技术难题。首先,针对传统A~*算法实时性差、消耗资源多等问题,将传统8邻域搜索方式改进为16方向搜索方式,并设计高匹配度启发函数和自适应权重系数全面提升路径规划算法性能;其次,设计了基于视觉反馈的面向空地协同作业场景下无人机自主降落策略,提高了自主降落的精度;最后,进行了仿真和实验,验证了所提改进A~*算法、自主降落和一体化实现策略的性能。结果表明,改进的A~*算法在规划路径长度与平滑度性能方面均得到提升,算法实时性大幅提升,满足复杂环境下的实时避障与规划需求;同时,无人机可以快速稳定地降落在地面平台目标点上。In air-ground collaborative operation scenarios,UAVs are required to have the capabilities of rapid path planning and accurate autonomous landing at the same time,which poses higher requirements on the real-time performance and accuracy of the algorithm under limited computing resources of the UAVs.This paper mainly solves the key technological problem of integrated realization of UAV rapid path planning and autonomous landing function.Firstly,to solve the problems of the traditional A*algorithm of bad real-time performance and abundant resource consumption,the traditional eight-neighborhood search approach is expanded to the sixteen-direction search approach,a high-matching-degree heuristic function is designed,and an adaptive weight coefficient is introduced to comprehensively enhance the performance of the path planning algorithm.Secondly,oriented to the scenario of air-ground collaborative operations,a UAV autonomous landing strategy based on visual feedback is designed,which improves the accuracy of autonomous landing.Finally,simulation and experiments are performed to verify the performance of the proposed enhanced A*algorithm,autonomous landing and the integrated realization strategy.The results show that the enhanced A*algorithm shortens the length of the planned path and improves the smoothness of the planned path,and the real-time performance of the algorithm is improved to a great extent,which meets the requirements of real-time obstacle avoidance and path planning in complex environments.Meanwhile,the UAV can quickly and steadily land at the target point on the ground platform.

关 键 词：空地协同 无人机 路径规划 改进A~*算法 自主降落 

分 类 号：V279[航空宇航科学与技术—飞行器设计] TP249[自动化与计算机技术—检测技术与自动化装置]