Distributed Sequential Task Allocation in Foraging Swarms

Abstract

Abstract-When designing a practical swarm robotics system, self-organized task allocation is key to make best use of resources. Current research in this area focuses on task allocation which is either distributed (tasks must be performed at different locations) or sequential (tasks are complex and must be split into simpler sub-tasks and processed in order). In practice, however, swarms will need to deal with tasks which are both distributed and sequential. In this paper, a classic foraging problem is extended to incorporate both distributed and sequential tasks. The problem is analysed theoretically, absolute limits on performance are derived, and a set of conditions for a successful algorithm are established. It is shown empirically that an algorithm which meets these conditions, by causing emergent cooperation between robots can achieve consistently high performance under a wide range of settings without the need for communication.

History-Based Response Threshold Model for Division of Labor in Multi-Agent Systems

“…A similar task allocation problem motivated by energy gain has also been previously studied [ 20 ]. In recent works, self-organized task allocation has been studied to handle tasks that are both distributed and sequential [ 21 ]. In a multi-foraging task, one or multiple objects are collected in complex environments.…”