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In this paper, the authors consider a robotic surveillance problem where a fixed remote station deploys a team of mobile robots to spatially explore a given workspace, detect an unknown number of static targets and inform the remote station of their findings. They are interested in designing trajectories (local motion decisions) for the robots that minimize the probability of target detection error at the remote station, while satisfying the requirements on the connectivity of the robots to the remote station. They show how such a design is possible by co-optimization of sensing (information gathering) and communication (information exchange) when motion planning.
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