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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机器人的多机器人系统的合作行为模型的鲁棒性:挖掘矿山应急灾害管理

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摘要

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:开发一个有效的现实生活模式模型一直是一种迅速增长的机器人研究区。地下隧道等环境是许多严苛的领域之一,仍然需要在现场机器人中的自主系统探索和开发。在本文中,换句话说,换句话说,提供了一种强大的合作框架,换句话说,在地下地形中的安全预防措施。该系统专为N-Robots而设计,以了解彼此的紧急情况和灾难行为并在避免碰撞的同时合作。该框架逻辑地建立了基于蚁群系统(ACS)和QLearning(QL)技术的QLACS模型。为了提供达到矿山前紧急灾害和灾害管理的强有力的方式,可扩展的QLAC用2机器人,3机器人和4机器人进行测试。性能评估结果表明,QLAC可在通信和搜索成本方面可靠地稳健,并且还可以扩展到基于N的MRS。

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