A Combination Positioning Method for Boom-Type Roadheaders Based on Binocular Vision and Inertial Navigation
A positioning method for a roadheader based on fiber-optic strap-down inertial navigation and binocular vision is proposed to address the issue of low measurement accuracy of the mining machine position caused by single-sensor methods in underground coal mines. A vision system for the mining machine...
| 發表在: | Machines |
|---|---|
| Main Authors: | , , , , , , |
| 格式: | Article |
| 語言: | 英语 |
| 出版: |
MDPI AG
2025-02-01
|
| 主題: | |
| 在線閱讀: | https://www.mdpi.com/2075-1702/13/2/128 |
| _version_ | 1849699025173872640 |
|---|---|
| author | Jiameng Cheng Dongjie Wang Jiming Liu Pengjiang Wang Weixiong Zheng Rui Li Miao Wu |
| author_facet | Jiameng Cheng Dongjie Wang Jiming Liu Pengjiang Wang Weixiong Zheng Rui Li Miao Wu |
| author_sort | Jiameng Cheng |
| collection | DOAJ |
| container_title | Machines |
| description | A positioning method for a roadheader based on fiber-optic strap-down inertial navigation and binocular vision is proposed to address the issue of low measurement accuracy of the mining machine position caused by single-sensor methods in underground coal mines. A vision system for the mining machine position is constructed based on the four-point target fixed on the body of the roadheader, and the position and attitude information of the roadheader are obtained by combining the inertial navigation on the body. To deal with the problem of position detection inaccuracies caused by the accumulation of errors in inertial navigation measurements over time and disturbances from body vibrations to the combined positioning system, an Adaptive Derivative Unscented Kalman Filtering (ADUKF) algorithm is proposed, which can suppress the impact of process variance uncertainties on the filtering. The simulation results demonstrate that, compared to the Unscented Kalman Filtering algorithm, the position errors in the three directions are reduced by 20%, 20.68%, and 28.57%, respectively. Experiments demonstrate that the method can compensate for the limitations of single-measurement methods and meet the positioning accuracy requirements for underground mining standards. |
| format | Article |
| id | doaj-art-eba702278c1944fcb45e440a88da4ab6 |
| institution | Directory of Open Access Journals |
| issn | 2075-1702 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| spelling | doaj-art-eba702278c1944fcb45e440a88da4ab62025-08-20T02:03:40ZengMDPI AGMachines2075-17022025-02-0113212810.3390/machines13020128A Combination Positioning Method for Boom-Type Roadheaders Based on Binocular Vision and Inertial NavigationJiameng Cheng0Dongjie Wang1Jiming Liu2Pengjiang Wang3Weixiong Zheng4Rui Li5Miao Wu6Department of Mechanical Engineering, School of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaDepartment of Mechanical Engineering, School of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaDepartment of Mechanical Engineering, School of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaChina Academy of Safety Science and Technology, Beijing 100012, ChinaDepartment of Energy and Power Engineering, School of Mechanical Engineering, Tsinghua University, Beijing 100084, ChinaBeijing Bluevision Science and Technology Co., Ltd., Beijing 100085, ChinaDepartment of Mechanical Engineering, School of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaA positioning method for a roadheader based on fiber-optic strap-down inertial navigation and binocular vision is proposed to address the issue of low measurement accuracy of the mining machine position caused by single-sensor methods in underground coal mines. A vision system for the mining machine position is constructed based on the four-point target fixed on the body of the roadheader, and the position and attitude information of the roadheader are obtained by combining the inertial navigation on the body. To deal with the problem of position detection inaccuracies caused by the accumulation of errors in inertial navigation measurements over time and disturbances from body vibrations to the combined positioning system, an Adaptive Derivative Unscented Kalman Filtering (ADUKF) algorithm is proposed, which can suppress the impact of process variance uncertainties on the filtering. The simulation results demonstrate that, compared to the Unscented Kalman Filtering algorithm, the position errors in the three directions are reduced by 20%, 20.68%, and 28.57%, respectively. Experiments demonstrate that the method can compensate for the limitations of single-measurement methods and meet the positioning accuracy requirements for underground mining standards.https://www.mdpi.com/2075-1702/13/2/128boom-type roadheaderfiber-optic inertial navigationbinocular visioncombined positioningKalman filtering |
| spellingShingle | Jiameng Cheng Dongjie Wang Jiming Liu Pengjiang Wang Weixiong Zheng Rui Li Miao Wu A Combination Positioning Method for Boom-Type Roadheaders Based on Binocular Vision and Inertial Navigation boom-type roadheader fiber-optic inertial navigation binocular vision combined positioning Kalman filtering |
| title | A Combination Positioning Method for Boom-Type Roadheaders Based on Binocular Vision and Inertial Navigation |
| title_full | A Combination Positioning Method for Boom-Type Roadheaders Based on Binocular Vision and Inertial Navigation |
| title_fullStr | A Combination Positioning Method for Boom-Type Roadheaders Based on Binocular Vision and Inertial Navigation |
| title_full_unstemmed | A Combination Positioning Method for Boom-Type Roadheaders Based on Binocular Vision and Inertial Navigation |
| title_short | A Combination Positioning Method for Boom-Type Roadheaders Based on Binocular Vision and Inertial Navigation |
| title_sort | combination positioning method for boom type roadheaders based on binocular vision and inertial navigation |
| topic | boom-type roadheader fiber-optic inertial navigation binocular vision combined positioning Kalman filtering |
| url | https://www.mdpi.com/2075-1702/13/2/128 |
| work_keys_str_mv | AT jiamengcheng acombinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation AT dongjiewang acombinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation AT jimingliu acombinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation AT pengjiangwang acombinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation AT weixiongzheng acombinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation AT ruili acombinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation AT miaowu acombinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation AT jiamengcheng combinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation AT dongjiewang combinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation AT jimingliu combinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation AT pengjiangwang combinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation AT weixiongzheng combinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation AT ruili combinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation AT miaowu combinationpositioningmethodforboomtyperoadheadersbasedonbinocularvisionandinertialnavigation |