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...kedly improved final configurations and faster convergence. A. Relation to Previous Work The basic coverage controller relevant to this work was first introduced in [1] in a non-adaptive form, and in =-=[6]-=- in an adaptive form. The ladybug exploration term can be included in either controller in essentially the same way. It was shown in [1] that coverage control can be phrased as a locational optimizati...

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...ensures global and local balance for part delivery. We describe decentralized control algorithms for the partition, part delivery, and assembling steps. The algorithms are inspired by the approach in =-=[2, 9, 7]-=- and use equal-mass partitioning as the optimization criterion. The algorithms rely on local information only (e.g. neighbors exchange information about their local mass). The task allocation and part...

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...ion. The distribution of sensory information in the environment is learned by adapting a parameter vector based on sensor measurements. The controller improves upon the one we previously presented in =-=[1]-=- by including a consensus term in the parameter adaptation laws to couple the adaptation among neighboring robots. The main effect of this coupling is that sensor measurements from any one robot propa...

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...mity. A common coverage control approach is through the definition of feedback control laws defined with respect to the centroids of Voronoi cells resulting from the Voronoi tessellation of an environment. In [7], the authors propose gradient descent-based individual robot control laws that guarantee optimal coverage of a convex environment given a density function which represents the desired coverage distribution. The authors of [8] build upon this idea and develop decentralized control laws that position a mobile sensor network optimally with respect to a known probability distribution. In [9], this approach is extended to consider nearoptimal controllers that do not require prior knowledge of a desired coverage distribution. To address the limitation of requiring a convex environment, the authors of [10] propose the use of geodesic Voronoi tessellations determined by the geodesic distance rather than the Euclidean distance. An approach that considers both exploration and coverage using Voronoi tessellations is presented in [11]. However, this method differs greatly from ours and assumes that the boundary of the environment is known. The Voronoi tessellation is computed based on th...

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...ids [16], [14]. A closely related problem is that of environment coverage [3], [10], and decentralised control laws have been derived that lead to near-optimal sensing coverage of a given environment =-=[13]-=-. Many such approaches have proven effective at maintaining team connectivity. However, some environments may contain significant interference, or may extend beyond team communication limits even when...

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...hing space once enables the robot to find the target. Since the worst case for the searching time is the time to cover the entire searching space, the searching problem becomes a coverage problem [2]–=-=[4]-=-. For a known environment, a coverage problem for a single robot often employs different approaches to decompose the searching space and output a continuous path that allows the robot to cover the ent...