Abstract Recent advancements in sensing and robotic technologies facilitate the use of on-demand building service robots in the built environment. Multi-robot based systems have arguably more advantages when compared to fixed sensor-based and single-robot based systems. These task-oriented building service robots face several challenges, such as task-allocation and route-planning. Previous studies adopted approaches from other domains, such as outdoor logistics, and made application-specific assumptions. This study proposes a new methodology to optimize the task-allocation and route-planning for multiple indoor robots with multiple starts and destination depots where each robot begins and ends at the same depot (referred to as a fixed destination multi-depot multiple traveling salesman problem-fMmTSP). The performance of the proposed algorithm was compared with two existing outdoor-based algorithms. Results show that the proposed algorithm performs better in almost all the cases for the assumed network, which supports the need to develop algorithms specifically for indoor networks.

中文翻译：

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室内建筑环境中多车位机器人的广义任务分配和路线规划

摘要 传感和机器人技术的最新进展促进了在建筑环境中使用按需建筑服务机器人。与基于固定传感器和基于单机器人的系统相比，基于多机器人的系统可以说具有更多优势。这些以任务为导向的建筑服务机器人面临着几个挑战，例如任务分配和路线规划。以前的研究采用了其他领域的方法，例如户外物流，并做出了针对特定应用的假设。本研究提出了一种新的方法来优化具有多个起点和终点站的多个室内机器人的任务分配和路线规划，其中每个机器人起点和终点都在同一个站台（称为固定目的地多站台多旅行商问题） -fMmTSP）。将所提出算法的性能与两种现有的基于户外的算法进行了比较。结果表明，所提出的算法在假设网络的几乎所有情况下都表现得更好，这支持开发专门针对室内网络的算法的需要。