@inproceedings{c9c90b71a3724c94bd9b05102eb4254b,
title = "A Path Planning for One UAV Based on Geometric Algorithm",
abstract = "In this paper, a new learning algorithm named geometric learning algorithm is proposed to solve the UAV's track planning problem. Actually, based on the environment modeling, the optimal path planning problem is to find an optimal route. The Geometric learning algorithm is essentially an reinforcement learning algorithm. It can not only fully use the distance information to calculate the track based on the geometric distance information but can also fuse dangerous information in a complex environment, which solves the problem of track planning from a practical and theoretical point of view. Based on the two-dimensional successful planning of a single drone, the algorithm is extended to the path planning and decision making of single drone three-dimensional planning. And from a practical and theoretical point of view, the path planning problem has been well solved.",
keywords = "Geometric learning, Unmanned aerial vehicles, path planning, real-time",
author = "Haochen Li and Wu, \{Sen Tang\} and Pengzhi Xie and Zekui Qin and Baochang Zhang",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018 ; Conference date: 10-08-2018 Through 12-08-2018",
year = "2018",
month = aug,
doi = "10.1109/GNCC42960.2018.9019122",
language = "英语",
series = "2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018",
address = "美国",
}