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Potential Game Based Distributed Control for Voronoi Coverage Problems with Obstacle Avoidance

机译:基于博弈的分布式控制在Voronoi覆盖避障问题中的潜在优势

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It is known that the optimal sensor coverage of a mission space is performed by a Voronoi partition, which is called a Voronoi coverage problem. We consider the case that the mission space has several obstacles where mobile sensors cannot be deployed and search an optimal deployment to maximize the sensing performance. Inspired by the potential field method, we introduce a repulsive potential for obstacle avoidance and define the objective function by a combination of two functions: one for evaluation of the sensing performance and the other for obstacle avoidance. We introduce a space where a sensor can move, called its moving space. In general, a moving space may not coincide with the mission space. We assume that the respective moving spaces of each sensor may differ from each other. By introducing a barycentric coordinate over the moving space, we show that the Voronoi coverage problem to maximize the objective function is transformed into a potential game. In potential games, local maximizers of a potential function are stable equilibrium points of the corresponding replicator dynamics. We propose a distributed sensor coverage control method based on the replicator dynamics to search a local maximizer of the objective function and a path to it. Using simulations, we also compare the proposed method with the Lloyd and TangentBug algorithm proposed by Breitenmoser et al.
机译:众所周知,任务空间的最佳传感器覆盖是由 Voronoi 分区执行的,这称为 Voronoi 覆盖问题。我们考虑了任务空间存在无法部署移动传感器的几个障碍,并寻找最佳部署以最大限度地提高传感性能。受势场法的启发,我们引入了避障的排斥势,并通过两个函数的组合来定义目标函数:一个用于评估感知性能,另一个用于避障。我们引入了一个传感器可以移动的空间,称为其移动空间。一般来说,移动空间可能与任务空间不一致。我们假设每个传感器的各自移动空间可能彼此不同。通过在移动空间上引入重心坐标,我们证明了最大化目标函数的 Voronoi 覆盖率问题被转化为一个潜在的博弈。在势博弈中,势函数的局部最大化是相应复制器动力学的稳定平衡点。我们提出了一种基于复制器动力学的分布式传感器覆盖控制方法,以搜索目标函数的局部最大化器及其路径。通过仿真,我们还将所提出的方法与Breitenmoser等人提出的Lloyd和TangentBug算法进行了比较。

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