A Cluster-based Approach to Consensus Based Distributed Task Allocation

This paper presents a novel extension to the Consensus-Based Bundle Algorithm (CBBA), which we have named Cluster-Formed Consensus-Based Bundle Algorithm (CF-CBBA). CF-CBBA is designed to reduce the amount of communication required to complete a distributed task allocation process, by partitioning the problem and processing it in parallel clusters. CF-CBBA has been shown, in comparison with baseline CBBA, to require less communication when allocating tasks. Three key aspects of task allocation have been investigated; (a) the time taken to allocate tasks, (b) the amount of communication necessary to satisfy the requirements of distributed task allocation algorithms such as CBBA, and (c) the efficiency with which a collection of tasks (a mission) is completed by a group of robots (a collective).