论文标题

将基于市场的多机器人任务分配应用于救护车派遣

The Application of Market-based Multi-Robot Task Allocation to Ambulance Dispatch

论文作者

Schneider, Eric, Poulton, Marcus, Drake, Archie, Smith, Leanne, Roussos, George, Parsons, Simon, Sklar, Elizabeth I

论文摘要

多机器人任务分配(MRTA)是将一组任务分配给机器人团队的问题,目的是优化某些标准,例如最大程度地减少完成所有任务或最大化团队联合活动效率所花费的时间或精力。 MRTA方法的探索通常仅限于实验室和现场实验。现有的现实世界模型很少,其中“在野外”部署了自动移动机器人团队,例如在工业环境中。在此处介绍的工作中,采用基于市场的MRTA方法适用于救护车派遣问题,在该问题中,救护车被分配以应对患者寻求帮助的响应。救护车和机器人有限(也许很少),专门的移动资源;事件和任务代表时间敏感,特定,潜在的无限,精确的对资源提供的服务的要求。伦敦救护车服务的历史数据描述了一组超过100万事件(匿名)事件,以评估基于市场的方法的预测性能与当前的手动,将救护车分配给事件的预测性能。实验结果表明,使用基于市场的方法时,响应时间的统计学显着改善。

Multi-Robot Task Allocation (MRTA) is the problem of distributing a set of tasks to a team of robots with the objective of optimising some criteria, such as minimising the amount of time or energy spent to complete all the tasks or maximising the efficiency of the team's joint activity. The exploration of MRTA methods is typically restricted to laboratory and field experimentation. There are few existing real-world models in which teams of autonomous mobile robots are deployed "in the wild", e.g., in industrial settings. In the work presented here, a market-based MRTA approach is applied to the problem of ambulance dispatch, where ambulances are allocated in respond to patients' calls for help. Ambulances and robots are limited (and perhaps scarce), specialised mobile resources; incidents and tasks represent time-sensitive, specific, potentially unlimited, precisely-located demands for the services which the resources provide. Historical data from the London Ambulance Service describing a set of more than 1 million (anonymised) incidents are used as the basis for evaluating the predicted performance of the market-based approach versus the current, largely manual, method of allocating ambulances to incidents. Experimental results show statistically significant improvement in response times when using the market-based approach.

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