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QoS-aware task distribution to a team of robots: an healthcare case study

机译:QoS任务分配给机器人团队:医疗案例研究

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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.
机译:在过去的几年中,我们通过在患者日常生活中采用机器人设备来协助增加医疗保健设施。在这些情况下,为了限制紧急情况的发生,监视患者状态所需的时间是至关重要的问题。因此,采用多机器人系统(MRS)可以缩短执行关键任务的时间,这使其在该领域的适用性不断提高。为了受益于采用MRS,需要一种高效的任务分配算法。在MRS中,通常会考虑使用诸如拍卖和谈判之类的基于市场的机制来在领域中进行有效的任务分配,在这些领域中,任务的特征在于质量参数,该质量参数取决于具体的机器人功能,与任务的执行方式有关。在这项工作中,我们提出了一种基于市场的协商机制,通过考虑完整分配应满足的质量参数的端到端要求,将任务分配给机器人团队。这些参数被视为要由各个机器人协商其值以满足端到端要求的商品。如果谈判成功,他们将获得任务分配。赋予机器人决定其提供的质量参数值的协商策略。这些策略旨在模拟市场的随机行为,并根据其功能考虑与当前机器人状态相关的动态信息。我们提出并讨论了在模拟医疗场景中采用建议的方法所获得的结果。

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