Geometric Reinforcement Learning for Path Planning of UAVs
文献类型：期刊论文
| 作者 | Zhang Baochang; Mao Zhili; Liu Wanquan; Liu Jianzhuang |
| 刊名 | JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
 |
| 出版日期 | 2015 |
| 英文摘要 | We proposed a new learning algorithm, named Geometric Reinforcement Learning (GRL), for path planning of Unmanned Aerial Vehicles (UAVs). The contributions of GRL are as: (1) GRL exploits a specific reward matrix, which is simple and efficient for path planning of multiple UAVs. The candidate points are selected from the region along the Geometric path from the current point to the target point. (2) The convergence of calculating the reward matrix is theoretically proven, and the path in terms of path length and risk measure can be calculated. (3) In GRL, the reward matrix is adaptively updated based on the Geometric distance and risk information shared by other UAVs. Extensive experimental results validate the effectiveness and feasibility of GRL on the navigation of UAVs |
| 收录类别 | SCI |
| 原文出处 | http://link.springer.com/article/10.1007/s10846-013-9901-z |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/6565]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS |
| 推荐引用方式 GB/T 7714 | Zhang Baochang,Mao Zhili,Liu Wanquan,et al. Geometric Reinforcement Learning for Path Planning of UAVs[J]. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS,2015. |
| APA | Zhang Baochang,Mao Zhili,Liu Wanquan,&Liu Jianzhuang.(2015).Geometric Reinforcement Learning for Path Planning of UAVs.JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS. |
| MLA | Zhang Baochang,et al."Geometric Reinforcement Learning for Path Planning of UAVs".JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS (2015). |
入库方式： OAI收割
来源：深圳先进技术研究院
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