Sensor network-based multi-robot task allocation

We present DINTA, distributed in-network task allocation - a novel paradigm for multi-robot task allocation (MRTA) where tasks are allocated implicitly to robots by a pre-deployed, static sensor network. Experimental results with a simulated alarm scenario show that our approach is able to compute solutions to the MRTA problem in a distributed fashion. We compared our approach to a strategy where robots use the deployed sensor network for efficient exploration. The data show that our approach outperforms such an exploration-only algorithm. The data also provide evidence that the proposed algorithm is more stable than the exploration-only algorithm.

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