With the advent of 6G technology, the demand for efficient and intelligent systems in industrial applications has surged, driving the need for advanced solutions in target localization. Utilizing swarm robots to locate unknown targets involves navigating increasingly complex environments. Digital Twinning (DT) offers a robust solution by creating a virtual replica of the physical world, which enhances the swarm's navigation capabilities. Our framework leverages DT and integrates Swarm Intelligence to store physical map information in the cloud, enabling robots to efficiently locate unknown targets. The simulation results demonstrate that the DT framework, augmented by Swarm Intelligence, significantly improves target location efficiency in obstacle-rich environments compared to traditional methods. This research underscores the potential of combining DT and Swarm Intelligence to advance the field of robotic navigation and target localization in complex industrial settings.

翻译：随着6G技术的到来，工业应用中对高效智能系统的需求激增，推动了对先进目标定位解决方案的需求。利用群体机器人定位未知目标需要在日益复杂的环境中导航。数字孪生通过创建物理世界的虚拟副本，为增强群体导航能力提供了稳健的解决方案。我们的框架利用数字孪生技术并集成群体智能，将物理地图信息存储于云端，使机器人能够高效定位未知目标。仿真结果表明，与传统方法相比，经群体智能增强的数字孪生框架在障碍物密集环境中显著提升了目标定位效率。本研究强调了结合数字孪生与群体智能在复杂工业场景中推动机器人导航与目标定位领域发展的潜力。