基于分布式连通性估计和控制的移动机器人协同覆盖

Xiaoli Li, Shuguang Zhao, Haiqin Xu
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引用次数: 1

摘要

本文研究了群中每个机器人只能在局部范围内感知和通信的离散时间连通覆盖问题。在该分布式框架中,通过引入最小时间一致性算法来估计连通性的代数参数,即拓扑拉普拉斯算子的第二小特征值,以保证较高的协作效率。由于没有强制保留某些边,因此保持第二最小特征值为正的方法为连接组中的机器人的运动保留了足够的自由度。在此基础上,提出了一种分散机器人的自部署算法,并保证每个时间步的第二最小特征值为正。最后,我们证明了该算法能够引导每对相邻机器人达到最大的目标距离。这意味着在连通性约束下实现了分布式最优覆盖。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cooperative coverage of mobile robots with distributed estimation and control of connectivity
This paper deals with the discrete-time connected coverage problem with the constraint that each robot of group can only sense and communicate in the local range. In such distributed framework, the algebraic parameter of connectivity, that is, the second smallest eigenvalue of topology Laplacian, is estimated by introducing the minimal-time consensus algorithm to guarantee the high cooperation efficiency. Since no certain edges are imposed to be preserved, the method of keeping the second smallest eigenvalue positive reserves a sufficient degree of freedom for the motion of robots in the connected group. Furthermore, a self-deployment algorithm is developed to disperse the robots with the precondition that the resulting second smallest eigenvalue keeps positive at each time-step. At last, we prove that the proposed algorithm steers each pair of neighbor robots to reach the largest objective distance from each other. It implies that the distributed optimal coverage is achieved under the connectivity constraint.
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