UWB localization of unmanned monorail crane with dual tags based on UKF weighted C-T fusion algorithm
Monorail cranes are crucial auxiliary transportation equipment in underground coal mines, currently advancing towards intelligent and unmanned operation. To enhance the precision of unmanned monorail crane positioning, research has been conducted on a dual-tag UWB positioning method based on the UKF...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Coal Science and Technology
2024-12-01
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| Series: | Meitan kexue jishu |
| Subjects: | |
| Online Access: | http://www.mtkxjs.com.cn/article/doi/10.12438/cst.2023-1082 |
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| Summary: | Monorail cranes are crucial auxiliary transportation equipment in underground coal mines, currently advancing towards intelligent and unmanned operation. To enhance the precision of unmanned monorail crane positioning, research has been conducted on a dual-tag UWB positioning method based on the UKF filtering and weighted C-T fusion algorithm. Firstly, considering the structural characteristics of monorail cranes, a dual-tag UWB positioning system was designed, comprising a dual-tag positioning information collection layer, positioning data transmission layer, and positioning coordinate resolution layer. Secondly, the Chan algorithm's UWB positioning results were employed as initial values for the Taylor algorithm, ensuring the convergence and com-putational efficiency of the Taylor algorithm. Additionally, by predefining the monorail crane length and obtaining positioning compensation error from dual-tag positioning data, the error was incorporated into the Taylor algorithm to further enhance positioning accuracy. Simulation results demonstrated a 44% improvement in positioning accuracy with the optimized algorithm.Subsequently, the Unscented Kalman Filter (UKF) was applied for filtering optimization of the weighted C-T fusion algorithm, enhancing the positioning system's accuracy in Non-Line-of-Sight (NLOS) environments. Simulation results indicated that the UKF-filtered opti-mization increased positioning accuracy by over 7.8% on straight segments and over 10.6% on curved segments. Moreover, as NLOS errors increased, positioning effectiveness significantly improved. Finally, real-world experiments were conducted in a coal mine monorail test field, revealing that the dual-tag weighted C-T fusion positioning algorithm based on UKF filtering achieved static positioning accuracy below 20 cm, dynamic positioning accuracy below 30 cm, and an overall positioning accuracy at the decimeter level. Stability and reliability were also enhanced, meeting the positioning requirements for unmanned monorail cranes in under-ground environments. The research on decimeter-level precision monorail crane positioning systems is crucial for the intelligent and unmanned efficient transportation of monorail cranes in mines. |
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| ISSN: | 0253-2336 |