Memory-Based Reinforcement Learning for Trans-Domain Tiltrotor Robot Control
文献类型：会议论文
| 作者 | Huo YJ(霍雨佳)1,2,3 ; Li YP(李一平)2,3; Feng XS(封锡盛)2,3
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| 出版日期 | 2019 |
| 会议日期 | December 26-28, 2019 |
| 会议地点 | Bangkok, Thailand |
| 页码 | 1-9 |
| 英文摘要 | Aiming at the problems of motion control with high precision for a new type of air-water trans-domain tiltrotors, a deep reinforcement learning controller is applied to these conditions. Reinforcement learning algorithm with memory capability allows the robot to learn from dynamic information collected in the past. In this paper, the trans-domain tiltrotors are supposed operating as a quad-rotors with fixed-wing in the air. Moreover, simulation is based on ROS and Gazebo platform for training the reinforcement learning repeatedly and the results demonstrate this algorithm gets better accuracy and effectiveness compared with other non-current methods in the conditions of the tiltrotors control task. |
| 产权排序 | 1 |
| 会议录 | 2019 10th Asia Conference on Mechanical and Aerospace Engineering
 |
| 会议录出版者 | IOP |
| 会议录出版地 | Bristol, UK |
| 语种 | 英语 |
| ISSN号 | 1742-6588 |
| WOS记录号 | WOS:000583802000011 |
| 源URL | [http://ir.sia.cn/handle/173321/26938]  |
| 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.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China |
| 推荐引用方式 GB/T 7714 | Huo YJ,Li YP,Feng XS. Memory-Based Reinforcement Learning for Trans-Domain Tiltrotor Robot Control[C]. 见:. Bangkok, Thailand. December 26-28, 2019. |
入库方式： OAI收割
来源：沈阳自动化研究所
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