A Survey of Indoor UAV Obstacle Avoidance Research

被引:11
|
作者
Li, Junlin
Xiong, Xingzhong [1 ]
Yan, Yuehao
Yang, Yunhong
机构
[1] Sichuan Univ Sci & Engn, Sch Automation & Informat Engn, Yibin 644000, Peoples R China
关键词
Collision avoidance; Cameras; Path planning; Drones; Aerospace control; Quadrotors; Optical flow; UAV; indoor obstacle avoidance; perception; obstacle detection; path planning; control; SLIDING MODE CONTROL; PATH; NAVIGATION; ALGORITHM; SYSTEM;
D O I
10.1109/ACCESS.2023.3262668
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
UAV obstacle avoidance technology is one of the key factors to realize UAV autonomous flight, efficient and accurate obstacle avoidance is significant to complete the UAV autonomous flight task. In contrast, the dynamic, real-time and uncertainty of the environment in which the UAV is located makes the problem very tricky, especially in the indoor environment. At present, a large number of scholars have shown strong interest in the indoor UAV obstacle avoidance problem. With the rapid development of computer technology and hardware devices, many intelligent algorithms have been proposed to solve the obstacle avoidance problem. However, the research on indoor UAV obstacle avoidance technology is not comprehensive enough, and there is a lack of summarization of the research results in recent years. This paper introduces the sensor modules commonly used for indoor UAV environment sensing, related obstacle avoidance methods based on sensory detection. Classifies and composes the commonly used UAV path planning obstacle avoidance algorithms, and gives several representative UAV flight control research methods. This paper summarizes the advantages and disadvantages of different perception modules and detection methods applied to UAV obstacle avoidance tasks, and compares various current path planning methods. Finally, the critical difficulties and challenges faced in the field of indoor UAV obstacle avoidance are discussed, and future research in the field of UAV obstacle avoidance has prospected.
引用
收藏
页码:51861 / 51891
页数:31
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