Mobile wireless sensor networks have the ability to monitor wide geographical areas. A suitable distribution of sensors can provide an optimal coverage (according to a predefined criterion) of the area of interest. On the other hand, mobile sensors can also move to the point of interest if necessary, thereby possibly leaving large regions vulnerable. In this paper we study how to balance optimal coverage with the need to quickly respond to an event. In particular, we show that by coordinating their actions, sensors can effectively estimate the location of a biochemical source while still providing a high level of coverage of the area of interest. We describe two switching control laws that achieve such a coordination and analyze their performance.
This paper presents a min-max algorithm for assigning mobile robots in a mobile wireless sensor network to different tasks that the network must perform. The algorithm minimizes the maximum penalty that is imposed when one of the tasks is not fully attended. The particular problem that we study is how to uniformly distribute autonomous mobile sensing robots inside a convex region while also quickly locating one or more sensory sources that might appear inside the region. The limited sensing capabilities of each robot suggest that several agents should collaborate to locate each source. The issue is then how to assign a sufficient number of robots to the sensing task and move them towards the source (even though some of them might initially not sense it), thereby diminishing the coverage of the region. We show that the proposed algorithm converges towards a stable equilibrium point. The algorithm is fully distributed and thus scalable. Simulation results that verify the theoretical claims are also presented.
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