離散質量分布を用いたMean Shift形状形成制御
Meanshift Shape Formation Control Using Discrete Mass Distribution
サンプル点上の離散質量分布で群れの形状をモデル化し、分散型Mean Shift制御則で複雑な形状形成と群れサイズ変化への適応を実現した。
詳しい要約
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著者: Yichen Cai, Yuan Gao, Pengpeng Li, Wei Wang, Guibin Sun, Jinhu Lü
分類: cs.RO
原文アブストラクト
The density-distribution method has recently become a promising paradigm owing to its adaptability to variations in swarm size. However, existing studies face practical challenges in achieving complex shape representation and decentralized implementation. This motivates us to develop a fully decentralized, distribution-based control strategy with the dual capability of forming complex shapes and adapting to swarm-size variations. Specifically, we first propose a discrete mass-distribution function defined over a set of sample points to model swarm formation. In contrast to the continuous density-distribution method, our model eliminates the requirement for defining continuous density functions-a task that is difficult for complex shapes. Second, we design a decentralized meanshift control law to coordinate the swarm's global distribution to fit the sample-point distribution by feeding back mass estimates. The mass estimates for all sample points are achieved by the robots in a decentralized manner via the designed mass estimator. It is shown that the mass estimates of the sample points can asymptotically converge to the true global values. To validate the proposed strategy, we conduct comprehensive simulations and real-world experiments to evaluate the efficiency of complex shape formation and adaptability to swarm-size variations.
