CASIA OpenIR  > 毕业生  > 硕士学位论文
Thesis Advisor谭民
Degree Grantor中国科学院研究生院
Place of Conferral北京
Keyword多机器人系统 任务分配 分层式组织结构 视觉感知 识别与跟踪
Other AbstractMulti-robot systems can accomplish complex tasks that cannot be completed by a single robot through the coordination among the robots, which is significant in both research and applications. Task assignment is the basis of cooperation among multiple robots, and the multi-robot system also needs to effectively integrate the visual information captured by each robot for the improvemnent of coordination. This thesis focuses on the task assignment and visual perception for multi-robot system. The contents are as follows:
Firstly, the research background and its significance of the multi-robot system task allocation and visual perception are given. Some typical examples of the multi-robot system are presented, and the research development of the task allocation and visual perception is then reviewed. The contents and structure of this thesis are also introduced.
Secondly, the task allocation method based on resource model and hierarchical framework is proposed. The proposed method establishes the rules for integration, comparison and matching of resources vectors. The hierarchical framework is built, which is composed of individual robots in the bottom layer and managers in higher layers. On this basis, the selection for robots as well as the bottom-up resources updating for each manager is executed according to the task resource constraint. Then the top-down resources comparison process between the task and the managers is used to generate candidate robot coalitions. Finally, the robot coalition with the optimal matching degree is selected to perform the task. The proposed approach can effectively deal with the challenges from complex tasks and large-scale multi-robot systems, and achieves a fast task allocation with optimal resources deployment, which are verified by simulations.
Thirdly, based on the target recognition method with feature fusion and the target tracking method with scale-adaptive for single robot, the visual perception method based on voting decision and adaptive updating of weights is proposed for multi-robot system. The voting decision mechanism of visual perception is made for multi-robot system, where for each robot, the voting weight and the feature measuring weight are updated according to the tracking confidence level and the measuring proportion, respectively. This solution can lead to a fact that the robot and feature with high accuracy dominate the visual perception process. The experimental results show that the proposed approach can realize the coordination of multi-robot system in target recognition and tracking with an improved accuracy of visual perception for multi-robot system.
Finally, the conclusions are given and future work is addressed.
Document Type学位论文
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
任亮. 多机器人系统任务分配与视觉感知研究[D]. 北京. 中国科学院研究生院,2018.
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