  In a multi-robot system, the appropriate allocation of the tasks to the
individual robots is a very significant component. The availability of a
centralized infrastructure can guarantee an optimal allocation of the tasks.
However, in many important scenarios such as search and rescue, exploration,
disaster-management, war-field, etc., on-the-fly allocation of the dynamic
tasks to the robots in a decentralized fashion is the only possible option.
Efficient communication among the robots plays a crucial role in any such
decentralized setting. Existing works on distributed Multi-Robot Task
Allocation (MRTA) either assume that the network is available or a naive
communication paradigm is used. On the contrary, in most of these scenarios,
the network infrastructure is either unstable or unavailable and ad-hoc
networking is the only resort. Recent developments in synchronous-transmission
(ST) based wireless communication protocols are shown to be more efficient than
the traditional asynchronous transmission-based protocols in ad hoc networks
such as Wireless Sensor Network (WSN)/Internet of Things (IoT) applications.
The current work is the first effort that utilizes ST for MRTA. Specifically,
we propose an algorithm that efficiently adapts ST-based many-to-many
interaction and minimizes the information exchange to reach a consensus for
task allocation. We showcase the efficacy of the proposed algorithm through an
extensive simulation-based study of its latency and energy-efficiency under
different settings.
