Tiltrotors Position Tracking Controller Design Using Deep Reinforcement Learning

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	Tiltrotors Position Tracking Controller Design Using Deep Reinforcement Learning
	Huo YJ(霍雨佳)1,2,3; Li YP(李一平)1,2; Feng XS(封锡盛)1,2
	2019
会议日期	December 12-15, 2019
会议地点	Sanya, China
关键词	deep reinforcement learning tiltrotors robot trans-domain robot position tracking
页码	1-9
英文摘要	In this paper, a quad-tiltrotors air-water trans-domain robot is introduced. The nonlinear dynamic behaviours with uncertainties require a robust controller for multi-tasks. For this robot, controllers are designed using deep reinforcement learning method solving position and attitude control when operating as a UAV in the air. A ROS combining Gazebo simulation platform is designed to train the robot. The simulation results show the tiltrotors robot gets capabilities of spots tracking as a quad-rotors, and trajectory tracking as both the quad-rotors and tiltrotors.
产权排序	1
会议录	2019 5th International Conference on Mechanical and Aeronautical Engineering (ICMAE 2019)
会议录出版者	IOP
会议录出版地	Bristol, UK
语种	英语
ISSN号	1757-8981
WOS记录号	WOS:000619388100047
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/26534]
专题	沈阳自动化研究所_水下机器人研究室
通讯作者	Huo YJ(霍雨佳)
作者单位	1.University of Chinese Academy of Sciences, Beijing, 100049, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China 3.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China
推荐引用方式 GB/T 7714	Huo YJ,Li YP,Feng XS. Tiltrotors Position Tracking Controller Design Using Deep Reinforcement Learning[C]. 见:. Sanya, China. December 12-15, 2019.