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A Murdoch-Based ROS Package for Multi-robot Task Allocation

机译:基于Murdoch的ROS包,用于多机器人任务分配

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Due to the rapid development of robotics application in a wide range of industries and the rapid growing complexity of tasks coordination, researches in Multi-Robot Task Allocation (MRTA) systems have increased swiftly in recent years. This work implemented an auction-based MRTA system using the MURDOCH architecture on ROS. Murdoch is an architecture which allows robots to place bids on tasks that they are capable of executing, and it selects the most fitted robot based on bids values calculated by a fitness function. The aim of this work is to present an adapted MURDOCH architecture that focused on proving a more generic MRTA solution, which may be applied to wider range of problems. Using ROS and a few other tools, our architecture was successfully validated, and it implemented this MURDOCH architecture in a readily scalable way. A few possible approaches for future improvements were also suggested.
机译:由于机器人在各种行业中的快速发展和任务协调的快速增长,多机器人任务分配(MRTA)系统的研究近年来迅速增加。这项工作在ROS上实现了一种基于拍卖的MRTA系统。 Murdoch是一种架构,允许机器人在他们能够执行的任务上放置出价,并且它基于由健身功能计算的出价值选择最适合的机器人。这项工作的目的是提供一种适应的默多普架构,其专注于证明更通用的MRTA解决方案,这可能适用于更广泛的问题。使用ROS和一些其他工具,我们的架构已成功验证,并以易于可扩展的方式实现了此默特架架构。还提出了一些未来改进的可能方法。

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