@inproceedings{32cb1af275f345d9bb05202fcdc3e0f3,
title = "3D G-learning in UAVs",
abstract = "In this paper, we focus on the learning strategy of path planning for Unmanned Aerial Vehicles (UAVs). We propose the G-Learning method to solve the problem of path planning in 3D and optimize the model algorithm. With G-Learning algorithm, the cost matrix can be calculated in real-time and adaptively updated based on the geometric distance and risk information shared with other UAVs. Extensive experimental results validate the effectiveness and feasibility of CGLA for safe navigation of multiple UAVs.",
keywords = "G-Learning, Path Planning, Q-Learning",
author = "Shangzhen Luan and Yun Yang and Hainan Wang and Baochang Zhang and Baoguo Yu and Chenglong He",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 12th IEEE Conference on Industrial Electronics and Applications, ICIEA 2017 ; Conference date: 18-06-2017 Through 20-06-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/ICIEA.2017.8282976",
language = "英语",
series = "Proceedings of the 2017 12th IEEE Conference on Industrial Electronics and Applications, ICIEA 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "953--957",
booktitle = "Proceedings of the 2017 12th IEEE Conference on Industrial Electronics and Applications, ICIEA 2017",
address = "美国",
}