Li, TengShin, HyosangTsourdos, Antonios2021-06-302021-06-302020-04-14Li T, Shin H-S, Tsourdos A. (2020) Threshold bundle-based task allocation for multiple aerial robots. IFAC-PapersOnLine, Volume 53, Issue 2, pp. 14787-147922405-8963https://doi.org/10.1016/j.ifacol.2020.12.1908https://dspace.lib.cranfield.ac.uk/handle/1826/16826This paper focuses on the large-scale task allocation problem for multiple Unmanned Aerial Vehicles (UAVs). One of the great challenges with task allocation is the NP-hardness for both computation and communication. This paper proposes an efficient decentralised task allocation algorithm for multiple UAVs to handle the NP-hardness while providing an optimality bound of solution quality. The proposed algorithm can reduce computational and communicating complexity by introducing a decreasing threshold and building task bundles based on the sequential greedy algorithm. The performance of the proposed algorithm is examined through Monte-Carlo simulations of a multi-target surveillance mission. Simulation results demonstrate that the proposed algorithm achieves similar solution quality compared with benchmark task allocation algorithms but consumes much less running time and consensus steps.enAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Multiple UAVstask allocationsubmodular maximisationthreshold bundlemulti-target surveillanceArticle