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Creators/Authors contains: "Bernardini, Francesco"

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  1. We present a heuristic method to construct an optimal communication network in an obstacle-dense environment. A set of immobile terminals must be connected by a network of straight-line edges by adding agents to serve as relays. Obstacles are represented by polygons, unaccessible by the agents of the network or by the edges. The problem with obstacles is reduced to a problem without obstacles by choosing the nodes of the optimal network among the obstacles’ vertices that are in mutual line of sight. A second heuristic method is developed to solve the bicriteria optimization problem with number of agents and length of the network as concurrent costs. 
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  2. We present strategies for realizing a swarm of mobile relays to provide a bi-directional wireless network that connects fixed terminals. Neither terminals or relays are permitted to transmit into disk-shaped no-transmission zones. We assume a planar environment and that each transmission area is a disk centered at the transmitter. We seek a strongly connected network between all terminals with minimal total cost, where the cost is the sum area of the transmission disks.Results for networks with increasing levels of complexity are provided. The solutions for local networks containing low numbers of relays and terminals are applied to larger networks. For more complex networks, algorithms for a minimum-spanning tree (MST) based procedure are implemented to reduce the solution cost. 
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  3. Magnetic induction localization is an inverse problem that determines the relative position and orientation (pose) between transmitting and receiving coils by analyzing the received signals. Related work has established methods to resolve the localization into two candidate poses. However, these methods require having signed signals, or periodic signals whose starting point is unambiguously determined with respect to an absolute reference (the transmitted signal). For distributed systems, the signal signs are difficult to resolve. This paper presents a method to extract partial information about the signs from unsigned signals. The method is tested in a hardware experiment. 
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