Affiliations: [a] Dipartimento di Matematica e Applicazioni, Università degli Studi di Napoli “Federico II”, Italy | [b] Dipartimento di Fisica, Università degli Studi di Napoli “Federico II”, Italy | [c] Dipartimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione, Università degli Studi di Napoli “Federico II”, Italy | [d] Istituto di Calcolo e Reti ad Alte Prestazioni, CNR, Italy
Correspondence:
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Corresponding author: Silvia Rossi, Dipertimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione, Università degli Studi di Napoli “Federico II”, via Claudio 21, 80125 Napoli, Italy. Tel.: +39081679963; E-mail: silvia.rossi@unina.it.
Abstract: In the last years, we assisted to an increase of healthcare facilities based on the adoption of robotic devices in patients daily life scenarios. In these contexts, the time needed to monitor the patients’ state is a crucial issue in order to limit the occurrence of emergencies. For this reason, the adoption of multi-robot systems (MRSs) allowing to shorten the time to perform critical tasks is growing its applicability in this field. In order to benefit of the adoption of an MRS, an efficient task allocation algorithm is required. The use of market-based mechanisms, such as auctions and negotiations, is often contemplated in MRS for efficient task allocation in domains where tasks are characterized by quality parameters that are related to the way the task is executed depending on the specific robot capabilities. In this work, we propose a market-based negotiation mechanism to allocate tasks to a team of robots, by taking into account end-to-end requirements that the complete allocation should meet in terms of the considered quality parameters. These parameters are considered as goods to be traded by individual robots that negotiate upon their values to meet the end-to-end requirements. In case of successful negotiation, they obtain the task assignment. Robots are endowed with negotiation strategies determining the quality parameter values they offer. These strategies are designed to simulate a stochastic behavior of the market, and they take into account dynamic information related to the current robot state depending on its functioning. We present and discuss the results obtained by adopting the proposed methodology within a simulated healthcare scenario.
Keywords: Multi-robot systems, robots in healthcare, market-based task allocation
