无人机辅助医院资产维护
Drones-aided Asset Maintenance in Hospitals
摘要：
2019冠状病毒病大流行的迅速爆发促使科学家和研究人员为未来的灾难做好准备。在疫情期间，全球医疗卫生当局强调物品及表面消毒的重要性。为于疫情期间提供高效及安全的消毒服务，室内资产已使用机器人。在本文中，我们设想使用无人机对医院和其他设施的户外资产进行消毒。这样的异构资产可以具有不同的服务需求（例如，使用时间、消毒材料的量等），而无人机通常具有有限的容量（即，行程时间、消毒剂携带能力）。为了以有效的方式为所有设施资产提供服务，必须优化无人机到资产的分配和无人机的旅行路线。在本文中，我们制定的能力限制车辆路径问题（CVRP），以找到最佳路线，为每个无人机，使总的服务时间最小化，而同时无人机满足的需求，每个资产分配给它。该问题是使用混合整数规划（MIP）解决。由于CVRP是一个NP难问题，我们提出了一个轻量级的启发式算法，以达到次优性能，同时降低了解决问题的时间复杂度，涉及大量的资产。
英文摘要：
The rapid outbreak of COVID-19 pandemic invoked scientists and researchers to prepare the world for future disasters. During the pandemic, global authorities on healthcare urged the importance of disinfection of objects and surfaces. To implement efficient and safe disinfection services during the pandemic, robots have been utilized for indoor assets. In this paper, we envision the use of drones for disinfection of outdoor assets in hospitals and other facilities. Such heterogeneous assets may have different service demands (e.g., service time, quantity of the disinfectant material etc.), whereas drones have typically limited capacity (i.e., travel time, disinfectant carrying capacity). To serve all the facility assets in an efficient manner, the drone to assets allocation and drone travel routes must be optimized. In this paper, we formulate the capacitated vehicle routing problem (CVRP) to find optimal route for each drone such that the total service time is minimized, while simultaneously the drones meet the demands of each asset allocated to it. The problem is solved using mixed integer programming (MIP). As CVRP is an NP-hard problem, we propose a lightweight heuristic to achieve sub-optimal performance while reducing the time complexity in solving the problem involving a large number of assets.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
