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Exploration and tracking by a team of robots have traditionally been considered as two separate problems solved in two phases: explore then track. This letter solves the multi-robot multi-object exploration and tracking problems simultaneously. A hierarchical architecture is used to coordinate robotic agents in the tracking of multiple objects of interest (OIs) while simultaneously allowing the task...
A significant generalization to the language-measure-theoretic path planning algorithm v* is presented that accounts for average dynamic uncertainties in plan execution. The planning problem thus can be solved with parametric input from the dynamics of the robotic platform under consideration. Applicability of the algorithm is demonstrated in a simulated maze solution and by experimental validation...
The v*-planning algorithm is generalized to handle finite memory obstacle dynamics. A sufficiently long observation sequence of obstacle dynamics is algorithmically compressed via symbolic dynamic filtering to obtain a probabilistic finite state model which is subsequently integrated with the navigation automaton to generate an overall model reflecting both navigation constraints and obstacle dynamics...
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