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Generalized task allocation and route planning for robots with multiple depots in indoor building environments

机译:室内建筑环境多仓库的机器人的广义任务分配与路径规划

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摘要

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.
机译:感应和机器人技术的最新进步有助于在建筑环境中使用按需建筑服务机器人。与固定的基于传感器和单机器人的系统相比,基于多机器人的系统具有更多优点。这些面向任务的建筑服务机器人面临着几种挑战,例如任务分配和路线规划。以前的研究采用其他域的方法,例如户外物流,并制定了特定于应用的假设。本研究提出了一种新的方法,可以优化多个室内机器人的任务分配和路线规划,其中多个启动和目的地仓库,其中每个机器人在同一仓库中开始并结束(称为固定目的地多仓销售商问题-fmmtsp)。将所提出的算法的性能与两个现有的户外基于算法进行比较。结果表明,该算法几乎所有案例都在假定网络的几乎所有情况下表现更好,这支持有必要开发专门用于室内网络的算法。

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