Andrew Adekunle

Papers

Total Citations

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About

Andrew Adekunle is a leading researcher in distributed multi-agent systems, with a particular focus on task allocation and coordination algorithms. His most influential work, "A Cluster-Based Approach to Consensus Based Distributed Task Allocation" (2014), introduces the Cluster-Formed Consensus-Based Bundle Algorithm (CF-CBBA), a novel extension of the widely-used Consensus-Based Bundle Algorithm. This contribution significantly reduces communication overhead in distributed task allocation by partitioning agents into clusters, enabling more efficient coordination in large-scale, decentralized networks. With over 30 citations, this paper has become a foundational reference for researchers working on scalable multi-robot systems and autonomous agent collaboration. Adekunle's work directly addresses critical challenges in real-world applications such as disaster response, surveillance, and autonomous exploration, where communication bandwidth is limited. His research continues to influence the development of robust, low-communication consensus protocols, making him a key figure in advancing the practical deployment of distributed autonomous systems.