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   With the development of robot technology and increasing potential applications, multi-robot systems have received much attention due to their flexibility, parallelism, and robustness. Multi-robot hunting is specifically researched due to its characteristics of antagonism and unpredicted motion of the invader. This thesis focuses on the research of multi-robot hunting in dynamic unknown environments. The contents are as follows:
Firstly, the research background and its significance of multi-robot systems are given. The research development and main research contents of multi-robot systems are introduced, and the representative multi-robot systems are demsontrated. Then multi-robot hunting is reviewed. The contents and structure of this thesis are also introduced. 
  Secondly, aiming at the problem of the encirclement points based hunting method with the prediction of the invader where the prediction step is empirically determined, a hunting approach based on dynamic prediction of target motion is proposed where the prediction step is optimized according to current environment. Based on the observed positions of the invader, its motion trajectory is acquired by cubic spline interpolation. Then, a series of encirclement points corresponding to different prediction steps are obtained. For each prediction step, the one-to-one mapping between the robots and encirclement points is established by minimizing the average distances. On this basis, an optimized prediction step is determined according to the variance of the distances between the robots and their respective encirclement points. Afterward, each robot obtains its desired encirclement point, and moves towards this point. After the robots basically arrive at their desired positions, they shrink to capture the target. The effectiveness of the proposed approach is verified by simulations.
  Thirdly, aiming at the problem of waiting effect caused by the encirclement points based multi-robot hunting method, a multi-robot fuzzy coordinated hunting approach based on regional division is proposed. Taking the invader as the center, the surrounding environment is divided into three zones according to the distance between the robot and the invader, and they are approaching zone, chasing zone and capturing zone. The robot in different zones shall adopt respective targeted solution. Based on the minimal angles formed among the robot, the invader, and the left and right nearest neighbors of the robot, L/R fuzzy PD controller and M fuzzy controller are designed to adjust the moving direction of the robot for coordinated hunting among the robots. The proposed approach is verified by simulations.
  Fourthly, an experimental platform of multi-robot system is built. The hardware components and control system are presented. The robot localization based on GPS, invader identification and positioning, as well as communication structure are then expounded, respectively. On this basis, the multi-robot experimental platform is tested.
  Finally, the conclusions are given and future work is listed.
Keyword多机器人系统 围捕 入侵者预测步数优化选取 围捕环境的区域划分 模糊协调围捕
Subject Area智能机器人
Document Type学位论文
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
吴志勇. 动态未知环境下多机器人协调围捕研究[D]. 北京. 中国科学院研究生院,2018.
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动态未知环境下多机器人协调围捕研究 .p(8589KB)学位论文 限制开放CC BY-NC-SA
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