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We present a near-optimal deterministic filter for systems that evolve on the unit circle. Unlike suboptimal filtering algorithms that rely on approximations of the system, the proposed approach preserves the non-linear system model. This leads to an explicit bound on the optimality gap in terms of the tracking error. Specifically, the optimality gap is bounded by a term that is fourth-order in the...
Exploration always occurs in the presence of uncertainty. In this paper, we consider path planning for autonomous vehicles equipped with range-based sensors and traveling in an uncertain area. The mission of the vehicles is to explore a set of objects of interest while reducing uncertainty in object position, visibility and state. A connection is shown between the Kalman filter (used to reduce uncertainty)...
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