An integrated decision-making framework of a heterogeneous aerial robotic swarm for cooperative tasks with minimum requirements

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dc.contributor.authorJang, Inmo
dc.contributor.authorShin, Hyo-Sang
dc.contributor.authorTsourdos, Antonios
dc.contributor.authorJeong, Junho
dc.contributor.authorKim, Seungkeun
dc.contributor.authorSuk, Jinoung
dc.date.accessioned2019-01-07T11:28:33Z
dc.date.available2019-01-07T11:28:33Z
dc.date.issued2018-05-15
dc.description.abstractGiven a cooperative mission consisting of multiple tasks spatially distributed, an aerial robotic swarm’s decision-making issues include team formation, team-to-task assignment, agent-to-work-position assignment and trajectory optimisation with collision avoidance. The problem becomes even more complicated when involving heterogeneous agents, tasks’ minimum requirements and fair allocation. This paper formulates all the combined issues as an optimisation problem and then proposes an integrated framework that addresses the problem in a decentralised fashion. We approximate and decouple the complex original problem into three subproblems (i.e. coalition formation, position allocation and path planning), which are sequentially addressed by three different proposed modules. The coalition formation module based on game theories deals with a max-min problem, the objective of which is to partition the agents into disjoint task-specific teams in a way that balances the agents’ work resources in proportion to the task’s minimum workload requirements. For agents assigned to the same task, given reasonable assumptions, the position allocation subproblem can be efficiently addressed in terms of computational complexity. For the trajectory optimisation, we utilise a Model Predictive Control and Sequential Convex Programming algorithm, which reduces the size of the problem so that the agents can generate collision-free trajectories on a real-time basis. As a proof of concept, we implement the framework into an unmanned aerial vehicle swarm’s cooperative stand-in jamming mission scenario and show its feasibility, fault tolerance and near-optimality based on numerical experiment.en_UK
dc.identifier.citationInmo Jang, Hyo-Sang Shin, Antonios Tsourdos, et al., An integrated decision-making framework of a heterogeneous aerial robotic swarm for cooperative tasks with minimum requirements. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, Volume 233, Issue 6, 2018, pp. 2101-2118en_UK
dc.identifier.issn0954-4100
dc.identifier.urihttps://doi.org/10.1177/0954410018772622
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/13785
dc.language.isoenen_UK
dc.publisherSAGEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectUnmanned aerial vehiclesen_UK
dc.subjectswarm roboticsen_UK
dc.subjectmission planningen_UK
dc.subjecttask allocationen_UK
dc.subjectcoalition formationen_UK
dc.subjectpath planningen_UK
dc.titleAn integrated decision-making framework of a heterogeneous aerial robotic swarm for cooperative tasks with minimum requirementsen_UK
dc.typeArticleen_UK

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