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Robustness of cooperative behaviour model on N robot-based multi-robot systems: Application to mine emergency and disaster management

机译:基于N个机器人的多机器人系统上协作行为模型的鲁棒性:在矿山应急和灾害管理中的应用

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Developing an efficient model for real-life management has been a rapidly growing robotic research area. Environments such as underground tunnels are one of many harsh areas that still need exploration and exploitation by autonomous systems in the field robotics. In this paper, a robust cooperative framework is presented for pre emergency and disaster management, in other words, safety prevention measures in the underground terrain. The system is designed for n-robots to understand the emergency and disaster behaviours of one another and cooperate while avoiding collision. The framework logically establishes a QLACS model based on Ant Colony System (ACS) and QLearning (QL) techniques. To provide a robust way of achieving pre-emergency and disaster management in the mine, the scalable QLACS was tested with 2-robots, 3-robots and 4-robots. The performance evaluation result shows that the QLACS is reliably robust in communication and search costs, and also scalable to n-based MRS.
机译:开发用于现实生活管理的有效模型一直是快速发展的机器人研究领域。诸如地下隧道之类的环境是仍然需要现场机器人技术中的自主系统进行探索和利用的许多恶劣区域之一。本文提出了一个强大的合作框架,用于应急和灾难管理,换句话说,就是在地下地形中的安全预防措施。该系统旨在让n机器人了解彼此的紧急情况和灾难行为,并在避免碰撞的情况下进行协作。该框架在逻辑上基于蚁群系统(ACS)和QLearning(QL)技术建立了QLACS模型。为了提供一种可靠的方法来实现矿井的事前和灾难管理,可伸缩QLACS已通过2机器人,3机器人和4机器人进行了测试。性能评估结果表明,QLACS在通信和搜索成本方面具有可靠的鲁棒性,并且可扩展到基于n的MRS。

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