We present a framework for distributed mobile sensor guidance to locate and track a target inside an urban environment. Our approach leverages the communications between robots when a link is available, but it also allows them to act independently. Each robot actively seeks the targetusinginformationmaximization.Therobotsareassumed tobecapableofcommunicatingwiththeirpeerswithinsome distance radius, and the sensor payload of each robot is a camera modeled to have target detection errors of types I and II. Our contributions include an optimal information fusionalgorithmfordiscretedistributionswhichallowseach agent to combine its local information with that of its neighbors, and a path planner that uses the fused estimate and a recentcoverageresultforinformationmaximizationtoguide the agents. We include simulations and laboratory experimentsinvolvingmultiplerobotssearchingforamovingtarget within model cities of different sizes.

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• Distributed information-based guidance of multiple mobile sensors for urban target search