Guiding attraction based random tree path planning under uncertainty: Dedicate for UAV
文献类型：会议论文
| 作者 | Yang L(杨亮) ; Qi JT(齐俊桐); Jiang ZY(江紫亚); Song DL(宋大雷); Han JD(韩建达)
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| 出版日期 | 2014 |
| 会议日期 | August 3-6, 2014 |
| 会议地点 | Tianjin, China |
| 关键词 | Algorithms Forestry Motion Planning Trees (Mathematics) |
| 页码 | 1182-1187 |
| 英文摘要 | This paper proposes a path planning algorithm called guiding attraction based random tree (GART), which is built upon the famous sampling-based algorithm RRT to generate a near optimal path in real time for unmanned aerial vehicle (UAV) navigation under uncertainty. The algorithm takes UAV heading dynamic constraint and 'obstacle safe attraction' into consideration, and uses a descriptive set method to describe the uncertainty caused by control and sensing error. The analysis shows that the computational complexity of GART is within a constant factor of RRT and RRT. A number of detailed comparisons of the proposed algorithm with RRT in 2D are given which verify the efficiency of our algorithm. Moreover, 3D simulation results demonstrate that GART find the near optimal path only after 2400 iterations, which means that GART outperformed RRT by 833%. © 2014 IEEE. |
| 产权排序 | 1 |
| 会议录 | 2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014
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| 会议录出版者 | IEEE Computer Society |
| 会议录出版地 | Washington, DC |
| 语种 | 英语 |
| ISBN号 | 978-1-4799-3978-7 |
| WOS记录号 | WOS:000366848100205 |
| 源URL | [http://ir.sia.cn/handle/173321/15153]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Yang L(杨亮) |
| 作者单位 | 1.Department of Electrical Engineering, City College, City University of New York, Convent Ave and 140th Street, New York NY, United States 2.University of Chinese Academy of Sciences, Beijing 100049, 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 | Yang L,Qi JT,Jiang ZY,et al. Guiding attraction based random tree path planning under uncertainty: Dedicate for UAV[C]. 见:. Tianjin, China. August 3-6, 2014. |
入库方式： OAI收割
来源：沈阳自动化研究所
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