作者：龚彧1, 刘晓宏1, 胥峥1, 丁楠1, 李明祖2, 邹振东3
作者单位：1. 盐城供电公司, 江苏 盐城 224005;
2. 南京工程学院电力学院, 江苏 南京 210095;
3. 南京理工大学机械工程学院, 江苏 南京 210094
关键词：无人机;自主避障;人工势场;路径跟踪
摘要：
针对无人机在三维空间中的路径跟踪和自主避障问题，提出一种基于改进三维人工势场法的无人机路径跟踪自主避障算法，算法以传统二维人工势场算法（apf）模型为基础，建立三维人工势场模型，以探测域的障碍存在判定和目标点分段方法，完成避障与跟踪模式的模式切换机制，为提高无人机在应对复杂障碍的自主避障能力，首先通过改进引力势场和斥力势场，解决目标不可达和障碍大小自适应问题，然后基于飞行路线的震荡判定，通过设定牵引目标点，解决局部极小问题。改进算法实现对原算法的功能扩充。对上述算法进行仿真模拟，在面型，凹形及复杂障碍场景下都完成规避任务，验证改进算法的有效性。
uav tracking and obstacle avoidance algorithm based on improved 3d apf
gong yu1, liu xiaohong1, xu zheng1, ding nan1, li mingzu2, zou zhendong3
1. yancheng power supply company, yancheng 224005, china;
2. school of electric power, nanjing institute of engineering, nanjing 210095, china;
3. school of mechanical engineering, nanjing university of science and technology, nanjing 210094, china
abstract: aiming at the problem of path tracking and autonomous obstacle avoidance of uav in three-dimensional space, this paper proposes an autonomous obstacle avoidance algorithm for uav path tracking based on the improved three-dimensional artificial potential field method. based on the traditional two-dimensional artificial potential field algorithm (apf) model, the three-dimensional artificial potential field model is established to determine the existence of obstacles in the detection domain and segment the target points, the mode switching mechanism of obstacle avoidance and tracking mode is completed. in order to improve the autonomous obstacle avoidance ability of uav in dealing with complex obstacles, the problems of target unreachable and obstacle size adaptation are solved by improving the gravitational potential field and repulsive potential field, and then the local minimum problem is solved by setting the traction target point based on the vibration judgment of flight route. the improved algorithm realizes the function expansion of the original algorithm. the above methods are simulated, and the avoidance tasks are completed in face, concave and complex obstacle scenes, which verifies the effectiveness of the improved algorithm
keywords: uav;utonomous obstacle avoidance;artificial potential field method;path tracking
2023, 49(6):100-106,129 收稿日期: 2021-12-23;收到修改稿日期: 2022-01-05
基金项目: 国家电网预研项目（j2021041）
作者简介: 龚彧(1973-),男,江苏淮安市人,工程师,硕士,从事电力系统自动化技术研究
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