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A self-organising cooperative hunting by robotic swarm based on particle swarm optimisation localisation

机译:基于粒子群优化定位的机器人群自组织协同狩猎

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摘要

A novel self-organising approach to cooperative hunting by robotic swarm is put forward. Each individual can simply detect the direction angle of moving target. By using particle swarm optimisation (PSO), locating target can be realised through the individual's local interaction. Collective hunting behaviour emerged when human object moved through the detection area. Simulations and experiments demonstrate the feasibility and effectiveness of the proposed approach to cooperative hunting by swarm robotic systems.
机译:提出了一种新颖的自组织机器人群协同狩猎方法。每个人都可以简单地检测到移动目标的方向角。通过使用粒子群优化(PSO),可以通过个体的局部交互来实现目标的定位。当人类物体穿过检测区域时,出现了集体狩猎行为。仿真和实验证明了所提出的群体机器人系统协同狩猎方法的可行性和有效性。

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