Abstract
Task allocation is a fundamental problem in multi-robot systems where heterogeneous robots cooperate to perform a complex mission. A general requirement in a task allocation algorithm is to find an optimal set of robots to execute a certain task. This paper describes how coordination capabilities of the space-based middleware are extended with the semantic model of robot capabilities to improve the process of selection in terms of flexibility, scalability and reduced communication overhead during task allocation. We developed a framework that translates resources into a newly defined semantic model and performs automatic reasoning to assist the task allocation. We conducted performance tests in a specific precision agriculture use case based on the robotic fleet for weed control elaborated within European Project RHEA-Robot Fleets for Highly Effective Agriculture and Forestry Management.
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Drenjanac, D., Klausner, L., Kühn, E., Tomic, S.D.K. (2013). Semantic Shared Spaces for Task Allocation in a Robotic Fleet for Precision Agriculture. In: Garoufallou, E., Greenberg, J. (eds) Metadata and Semantics Research. MTSR 2013. Communications in Computer and Information Science, vol 390. Springer, Cham. https://doi.org/10.1007/978-3-319-03437-9_43
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DOI: https://doi.org/10.1007/978-3-319-03437-9_43
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03436-2
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