@inproceedings{192ca4c46385473a8223b09be427a4a1,
title = "Hybrid path planning of a quadrotor UAV based on Q-Learning algorithm",
abstract = "The hybrid methodology is an emerging technology for control solution of nonlinear control systems with infinite states, moreover, by utilizing the approach the system can be transformed to a finite one based on discrete abstractions. In this paper, the problem of path planning of a quadrotor unmanned aerial vehicle (UAV) is investigated in the framework of hybrid methodology. With the kinematics model of the Quadrotor UAV and the abstraction of the environment in the form of grid world, the design procedure is presented by utilizing the Q-learning algorithm, which is one of the reinforcement method. In this process, an optimal or suboptimal safe flight trajectory will be obtained by learning constantly to maximize the reward. Matlab software is used for computation, and the effectiveness of the proposed method is illustrated by a typical example.",
keywords = "Hybrid System, Path Planning, Q-Learning, Quadrotor UAV",
author = "Tianze Zhang and Xin Huo and Songlin Chen and Baoqing Yang and Guojiang Zhang",
note = "Publisher Copyright: {\textcopyright} 2018 Technical Committee on Control Theory, Chinese Association of Automation.; 37th Chinese Control Conference, CCC 2018 ; Conference date: 25-07-2018 Through 27-07-2018",
year = "2018",
month = oct,
day = "5",
doi = "10.23919/ChiCC.2018.8482604",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "5415--5419",
editor = "Xin Chen and Qianchuan Zhao",
booktitle = "Proceedings of the 37th Chinese Control Conference, CCC 2018",
address = "美国",
}