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Multi-robot hunting in dynamic environments
Cao, Zhiqiang1; Gu, Nong2; Tan, Min1; Nahavandi, Saeid2; Mao, Xiaofeng3; Guan, Zhenying2
AbstractThis paper is concerned with multi-robot hunting in dynamic environments. A BCSLA approach is proposed to allow mobile robots to capture an intelligent evader. During the process of hunting, four states including dispersion-random-search, surrounding, catch and prediction are employed. In order to ensure each robot appropriate movement in each state, a series of strategies are developed in this paper. The dispersion-search strategy enables the robots to find the evader effectively. The leader-adjusting strategy aims to improve the hunting robots' response to environmental changes and the outflank strategy is proposed for the hunting robots to force the evader to enter a besieging circle. The catch strategy is designed for shrinking the besieging circle to catch the evader. The predict strategy allows the robots to predict the evader's position when they lose the tracking information about the evader. A novel collision-free motion strategy is also presented in this paper, which is called the direction-optimization strategy. To test the effect of cooperative hunting, the target to be captured owns a safety-motion strategy, which helps it to escape being captured. The computer simulations support the rationality of the approach.
KeywordMulti-robot Hunting Besieging Circle Dynamic Environment
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence
WOS IDWOS:000254981300006
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Chinese Acad Sci, Inst Automat, Lab Complex Syst & Intelligence Sci, Beijing 100080, Peoples R China
2.Deakin Univ, Sch Informat Technol & Engn, Geelong, Vic 3217, Australia
3.Penn State Univ, Dept Mech Engn, University Pk, PA 16802 USA
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Cao, Zhiqiang,Gu, Nong,Tan, Min,et al. Multi-robot hunting in dynamic environments[J]. INTELLIGENT AUTOMATION AND SOFT COMPUTING,2008,14(1):61-72.
APA Cao, Zhiqiang,Gu, Nong,Tan, Min,Nahavandi, Saeid,Mao, Xiaofeng,&Guan, Zhenying.(2008).Multi-robot hunting in dynamic environments.INTELLIGENT AUTOMATION AND SOFT COMPUTING,14(1),61-72.
MLA Cao, Zhiqiang,et al."Multi-robot hunting in dynamic environments".INTELLIGENT AUTOMATION AND SOFT COMPUTING 14.1(2008):61-72.
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