无人机碰撞规避路径规划算法研究 -- 西北工业大学学报,2019,37(1):100-106
论文:2019,Vol:37,Issue(1):100-106
引用本文:
徐钊, 胡劲文, 马云红, 王曼, 赵春晖. 无人机碰撞规避路径规划算法研究[J]. 西北工业大学学报
XU Zhao, HU Jinwen, MA Yunhong, WANG Man, ZHAO Chunhui. A Study on Path Planning Algorithms of UAV Collision Avoidance[J]. Northwestern polytechnical university

无人机碰撞规避路径规划算法研究
徐钊1, 胡劲文2, 马云红1, 王曼2, 赵春晖2
1. 西北工业大学 电子信息学院, 陕西 西安 710072;
2. 西北工业大学 自动化学院, 陕西 西安 710072
摘要:
无人机(unmanned aerial vehicle,UAV)技术是目前国内外的研究热点。无人机系统正向着智能化、自主化的方向发展,其中路径规划是无人机自主控制的重要组成部分及无人机飞行安全的重要保障。为优化无人机障碍规避路径规划算法,分别设立静态障碍物和动态障碍物环境,基于最小规避距离和航程比这2个指标,比较分析了人工势场法、模糊逻辑算法和蚁群算法对无人机碰撞规避路径规划的性能,并针对人工势场法易陷入局部极小值的缺陷提出了通过增加垂直引导斥力来使无人机逃离局部极小值的改进措施,实验仿真严谨可靠,为进一步融合多种算法、优化现有路径规划算法奠定了基础。
关键词:    无人机    蚁群算法    模糊逻辑    人工势场法    路径规划    碰撞规避   
A Study on Path Planning Algorithms of UAV Collision Avoidance
XU Zhao1, HU Jinwen2, MA Yunhong1, WANG Man2, ZHAO Chunhui2
1. School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China;
2. School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
Abstract:
The unmanned aerial vehicle (UAV) has been a research hotspot worldwide. The UAV system is developing to be more and more intelligent and autonomous. UAV path planning is an important part of UAV autonomous control and the important guarantee of UAV's safety. For the purpose of improving the collision avoidance and path planning algorithms, the artificial potential field, fuzzy logic algorithm and ant colony algorithm are simulated respectively in the static obstacle and dynamic obstacle environments, and compared based on the minimum avoidance distance and range ratio. Meanwhile, an improved algorithm of artificial potential field is proposed, and the improvement helps the UAV escape the local minimum by introducing the vertical guidance repulsion. The simulation results are rigorous and reliable, which lay a foundation for the further fusion of multiple algorithms and improving the path planning algorithms.
Key words:    unmanned aerial vehicles    artificial potential field    fuzzy logic algorithm    ant colony algorithm    path planning    collision avoidance   
收稿日期: 2018-03-06     修回日期:
DOI: 10.1051/jnwpu/20193710100
基金项目: 国家自然科学基金(61803309,61603303)、中国博士后基金(2017M610650,2018M633574,2018T111096)、爱生创新发展基金(ASN-IF2015-1502)与中央高校科研业务基本费(3102017JG02011)资助
通讯作者: 胡劲文(1983-),西北工业大学副教授,主要从事无人机传感器网络、多无人机网络控制研究。     Email:
作者简介: 徐钊(1982-),女,西北工业大学讲师,主要从事设备故障诊断、健康管理研究。
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