Currently in the literature there does not exist a framework which incorporates a heterogeneous team of agents to solve the sensor network connectivity problem. An approach that makes use of a heterogeneous team of agents has several advantages when cost, integration of capabilities, or possible large search areas need to be investigated. A heterogeneous team allows for the robots to become "specialized" in their abilities and therefore accomplish sub-goals more efficiently which in turn makes the overall mission more efficient.;In Part I of this dissertation we address the problem of prioritized sensing of an area with a homogeneous sensor network. We derive a decentralized and collision free controller that drives the sensing agents to positions within the area that contain the highest probability of containing "good information." We then apply this prioritized sensing controller to a target search scenario, where a group of cooperating UAVs must detect then track a maneuvering target within the search space.;In Part II of this dissertation we relax the assumption of network connectivity within the sensor network and introduce mobile communication relays to the network. This addition converts the homogeneous sensor network to a heterogeneous one. Based on the communication geometry of both sensing and communication relay agents we derive communication constraints within the network that guarantee network connectivity. We then define a heterogeneous proximity graph that encodes the communication links that exist within the heterogeneous network. By specifying particular edge weights in the proximity graph, we provide a technique for biasing particular connections within the heterogenous sensor network. Through a minimal spanning tree approach, we show how to minimize communication links within the network which allows for larger feasible motion sets of the sensing agents that guarantee the network remains connected. We also provide an algorithm that allows for adding communication links to the minimal spanning tree of the heterogeneous proximity graph to create a biconnected graph that is robust to a single node failure. We then combine the prioritized search algorithm from Part I and the communication constraints from Part II to provide a decentralized prioritized sensing control algorithm for a heterogenous sensor network that maintains network connectivity.;Lastly, in Part III we describe our robotic testbed that has been built to validate our proposed algorithms. We provide hardware experiments for both homogenous and heterogeneous sensor networks.
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