Exploring 6G Potential for Industrial Digital Twinning and Swarm Intelligence in Obstacle-Rich Environments

Autor:	Yuan, Siyu, Alam, Khurshid, Han, Bin, Krummacker, Dennis, Schotten, Hans D.
Rok vydání:	2024
Předmět:	Computer Science - Robotics Computer Science - Multiagent Systems
Druh dokumentu:	Working Paper
Popis:	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. Comment: Submitted to IEEE VTM
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2406.19930 Zobrazit plný text záznamu View this record from Arxiv