Cooperative and Geometric Learning for Path Planning of UAVs
文献类型：会议论文
| 作者 | Baochang Zhang; Zhili Mao; Wanquan Liu; Jianzhuang Liu; Zheng Zheng |
| 出版日期 | 2013 |
| 会议名称 | 2013 International Conference on Unmanned Aircraft Systems |
| 会议地点 | Atlanta, GA, United states |
| 英文摘要 | We propose a new learning algorithm, named Cooperative and Geometric Learning (CGL), to solve maneuverability, collision avoidance and information sharing problems in path planning for Unmanned Aerial Vehicles (UAVs). The contributions of CGL are threefold: 1) CGL exploits a specific reward matrix G, which leads to a simple and efficient algorithm for the path planning of multiple UAVs. 2) The optimal path in terms of path length and risk measure from a given point to the target point can be calculated. 3) In CGL, the reward matrix G is calculated in real-time and adaptively updated based on the geometric distance and risk information shared by other UAVs. Extensive experimental results validate the effectiveness and feasibility of CGL on the navigation of UAVs. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/4480]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2013 |
| 推荐引用方式 GB/T 7714 | Baochang Zhang,Zhili Mao,Wanquan Liu,et al. Cooperative and Geometric Learning for Path Planning of UAVs[C]. 见:2013 International Conference on Unmanned Aircraft Systems. Atlanta, GA, United states. |
入库方式： OAI收割
来源：深圳先进技术研究院
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