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We define and discuss a class of multi-robot systems possessing ergodic dynamics and show that they are realizable on physical hardware and useful for a variety of tasks while being amenable to analysis. We describe robot controllers synthesized to possess these dynamics and also physics-based methodologies that allow macroscopic structures to be uncovered and exploited for task execution in systems...
We address the problem of finding the optimal assignment of tasks to a team of robots when the associated costs may vary, which arises when robots deal with uncertain or dynamic situations. We detail how to compute a sensitivity analysis that characterizes how much costs may change before optimality is violated. Using this analysis, robots are able to avoid unnecessary re-assignment computations and...
A task-executing robot may encounter various types of uncertainty born of sensing, actuation, and motion errors. A robot uncertain of its current state is likely to reflect this uncertainty in the calculation of its utilities or performance estimates (e.g., costs, fitnesses) for planning purposes too. While controlling a single robot under uncertainty is challenging, coordinating a group of robots...
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