Self-Adaptive pattern formation with battery-powered robot swarms
文献类型：会议论文
| 作者 | Svogor, Ivan; Beltrame, Giovanni; Li GN(李冠男)
|
| 出版日期 | 2017 |
| 会议名称 | 2017 NASA/ESA Conference on Adaptive Hardware and Systems, AHS 2017 |
| 会议日期 | July 24-27, 2017 |
| 会议地点 | Pasadena, CA, USA |
| 页码 | 253-260 |
| 通讯作者 | Li GN(李冠男) |
| 中文摘要 | This paper presents a distributed, energy-Aware algorithm for an autonomous deployment of battery-powered robots in a specified pattern. While each robot gradually discharges and leaves the formation to recharge, the algorithm presented in this paper assures that the formation pattern is preserved. This is achieved by defining the desired pattern as a point cloud where each point is occupied by a robot. The point cloud is transformed into a tree model that is shared among all robots. This model is used by each robot independently to govern its behavior, resulting in a self-Adaptive network of robots which automatically generate paths for joining the formation and leaving it to recharge. Robots which leave the formation are replaced by neighbors to preserve the formation pattern. To demonstrate our algorithm we use a physics-based simulator and evaluate the persistence of the pattern formation formed by a robot swarm in an environment without global positioning, using only range and bearing. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议录 | 2017 NASA/ESA Conference on Adaptive Hardware and Systems, AHS 2017
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-5386-3439-4 |
| WOS记录号 | WOS:000427173400035 |
| 源URL | [http://ir.sia.cn/handle/173321/21236]  |
| 专题 | 沈阳自动化研究所_海洋信息技术装备中心 |
| 作者单位 | 1.State Key Laboratory of Robotics, Shenyang Institute of Automation, University of Chinese Academy of Sciences, Beijing, China 2.Department of Computer and Software Engineering, Polytechnique Montréal, Montréal, QC, Canada |
| 推荐引用方式 GB/T 7714 | Svogor, Ivan,Beltrame, Giovanni,Li GN. Self-Adaptive pattern formation with battery-powered robot swarms[C]. 见:2017 NASA/ESA Conference on Adaptive Hardware and Systems, AHS 2017. Pasadena, CA, USA. July 24-27, 2017. |
入库方式： OAI收割
来源：沈阳自动化研究所
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