Task Variant Allocation in Distributed Robotics

This paper tackles the problem of allocating tasks to a distributed heterogeneous robotic system, where tasks---named *task variants* in the paper---can vary in terms of trade-off between resource requirements and quality of service provided. Three different methods (constraint programming, greedy, and metaheuristic) are proposed to solve such a problem and are evaluated both in simulation and in a real scenario, showing the goodness of the constraint programming method.

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