Sold!: auction methods for multirobot coordination

TLDR

Cooperation is essential for unlocking the potential of multirobot systems. The study seeks to enable cooperation among failure‑prone autonomous robots in noisy, dynamic settings by proposing a dynamic task allocation method. MURDOCH is an auction‑based task allocation system built on a resource‑centric publish/subscribe model, a variant of the Contract Net Protocol that approximates a global optimum, and was validated in both tightly coupled manipulation and loosely coupled long‑term autonomy experiments. Empirical results demonstrate that MURDOCH’s distributed negotiation effectively coordinates physical multirobot systems.

Abstract

The key to utilizing the potential of multirobot systems is cooperation. How can we achieve cooperation in systems composed of failure-prone autonomous robots operating in noisy, dynamic environments? We present a method of dynamic task allocation for groups of such robots. We implemented and tested an auction-based task allocation system which we call MURDOCH, built upon a principled, resource centric, publish/subscribe communication model. A variant of the Contract Net Protocol, MURDOCH produces a distributed approximation to a global optimum of resource usage. We validated MURDOCH in two very different domains: a tightly coupled multirobot physical manipulation task and a loosely coupled multirobot experiment in long-term autonomy. The primary contribution of the paper is to show empirically that distributed negotiation mechanisms such as MURDOCH are viable and effective for coordinating physical multirobot systems.