Hybrid Information and Plan Consensus in Distributed Task Allocation

Many missions envisioned in future operations will require that teams of autonomous agents (e.g., unmanned aerial vehicles) maintain a high degree of coordination to efficiently execute required tasks. Achieving these desired levels of coordination will be particularly challenging in contested environments in which the communications may, as a result of jamming, environment conditions, or terrain, be unavailable, unreliable, have high latency, or high cost. This paper introduces a new planning paradigm that combines plan consensus with implicit coordination to enable a higher degree of coordination and produce plans faster than would be available by either method separately. Results in the paper show reductions in number of messages, convergence iterations and number of overall plan conflicts during the algorithmic convergence process for certain planning environments.