Exploring 6G Potential for Industrial Digital Twinning and Swarm Intelligence in Obstacle-Rich Environments
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866913959365312512 |
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| author | Yuan, Siyu Alam, Khurshid Han, Bin Krummacker, Dennis Schotten, Hans D. |
| author_facet | Yuan, Siyu Alam, Khurshid Han, Bin Krummacker, Dennis Schotten, Hans D. |
| contents | With the advent of Sixth Generation (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 twin (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 (SI) 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 SI, 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_19930 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Exploring 6G Potential for Industrial Digital Twinning and Swarm Intelligence in Obstacle-Rich Environments Yuan, Siyu Alam, Khurshid Han, Bin Krummacker, Dennis Schotten, Hans D. Robotics Multiagent Systems With the advent of Sixth Generation (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 twin (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 (SI) 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 SI, 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. |
| title | Exploring 6G Potential for Industrial Digital Twinning and Swarm Intelligence in Obstacle-Rich Environments |
| topic | Robotics Multiagent Systems |
| url | https://arxiv.org/abs/2406.19930 |