An adaptive task assignment method for multiple mobile robots via swarm intelligence approach
文献类型：会议论文
| 作者 | Zhang, Danda; Xie, Guangmin; Yu, Junzhi ; Wang, Lon; Zhang, Dandan
|
| 出版日期 | 2005 |
| 会议日期 | June 27, 2005 - June 30, 2005 |
| 会议地点 | Espoo, Finland |
| 关键词 | Task Assignment Learning Swarm Intelligence |
| 英文摘要 | This paper describes an adaptive task assignment method for a team of fully distributed mobile robots with initially identical functionalities in unknown environments. The method is applicable for mediate- to large-scaled robot groups and tasks. A hierarchical architecture for task assignment is established for each individual robot. In the higher hierarchy, the self-reinforcement learning model inspired by the behaviors of social insects is employed to differentiate the initially identical robots into different kinds of high-level task "specialists"; while in the lower hierarchy, Ant System algorithm is adopted to organize low-level task assignment. To avoid using a centralized component, "local blackboard" communication mechanism is utilized for knowledge sharing. The proposed method allows the robot team members to adapt themselves to the unknown dynamic environments, respond flexibly to the environment perturbations and robustly to the modifications in the team arising from mechanical failure. Simulations of a cooperative collection task validate the effectiveness of the presented method. |
| 会议录 | IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/13152]  |
| 专题 | 自动化研究所_个人空间 |
| 通讯作者 | Zhang, Dandan |
| 作者单位 | Department of Mechanics and Engineering Science, Center for Systems and Control, Peking University, Beijing, 100871, China |
| 推荐引用方式 GB/T 7714 | Zhang, Danda,Xie, Guangmin,Yu, Junzhi,et al. An adaptive task assignment method for multiple mobile robots via swarm intelligence approach[C]. 见:. Espoo, Finland. June 27, 2005 - June 30, 2005. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。