Research on the Body Positioning Method of Bolting Robots Based on Monocular Vision
Source abstract
Abstract
Aiming at the intelligent design of underground roadway support and the precise positioning of unmanned full excavation faces, a positioning and measurement method of bolt robots based on the monocular vision principle was proposed. In this paper, a vehicle body positioning model based on image data was established. The data were obtained with a camera, and the conversion between image coordinates and world coordinates was carried out through coordinate system conversion. A monocular vision positioning system of the bolt robot was designed, and the simulation’s experimental model was established. Under the simulation’s experimental conditions, the effective positioning distance of the monocular vision positioning system was measured. An experimental platform for the bolt robot was designed, and real-time human positioning data measurement of the vehicle was carried out. The experimental error was analyzed, and the reliability of the method was proven. This method realizes the real-time positioning of underground mines through the bolt robot, improves the accuracy and efficiency of the positioning, and lays a foundation for the positioning control of the heading face and the unmanned bolt robot.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Power Line Inspection Robots · Robotics and Sensor-Based Localization · Robotic Path Planning Algorithms
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Mechanical and Electrical Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
Key Laboratory of Intelligent Mining and Robotics, Ministry of Emergency Management, Beijing 100083, China
Beijing Institute of Control and Electronics Technology, Beijing 100038, China
Beijing Tianma Intelligent Control Technology Co., Ltd., Beijing 100029, China
Funding
the Innovation Research Group Project of the National Natural Science Foundation of China · National Key Research and Development Program of China · Key Research and Development Program of Hebei Province
References (27)
Show source-provided references
1. Analysis of the current situation and disaster prevention and control of deep mining in China’s coal mines
2. Cascade construction and key technologies of geological model for intelligent and precise coal mining face
3. Development of coal mine intelligence and its technical equipment
4. Binocular vision-based displacement detection method for anchor digging robot
5. Present situation and development direction of navigation technology of boom-type roadheader
6. Ultra-Wideband pose detection system for boom-type roadheader based on caffery transform and taylor series expansion10.1088/1361-6501/aa91c0 ↗
7. Research on the key technology of autonomous positioning of mining cantilever roadheader based on machine vision
8. Research on real-time positioning measurement method of road header based on vision/inertial navigation
9. Mathematical model of automatic positioning of coal road bolt drilling rig
10. Research on robot visual image enhancement and obstacle recognition in coal mine roadway environment
11. Talking about the application prospect of machine vision technology in coal mines
12. Research on Automatic Positioning Drilling Technology of Tunnel Rock Drill Trolley
13. Application Status and Trend of Machine Vision in Coal Machinery Equipment
14. Low-luminance image enhancement algorithm for coal mine underground based on double gamma function
15. Vision positioning technology of mobile robot based on adaptive down sampling
16. Vision-based distributed formation control without an external positioning system10.1109/TRO.2016.2523542 ↗
17. Aref, M.M., Oftadeh, R., Ghabcheloo, R., and Mattila, J. (2016, January 21–25). Real-time vision-based navigation for nonholonomic mobile robots. Proceedings of the 2016 IEEE International Conference on Automation Science and Engineering (CASE), Fort Worth, TX, USA.10.1109/COASE.2016.7743449 ↗
18. Mobile robot location algorithm based on image processing technology
19. Huang, C., Chen, D., and Tang, X. (2015, January 12–13). Implementation of Workpiece Recognition and Location Based on Opencv. Proceedings of the 2015 8th International Symposium on Computational Intelligence and Design (ISCID), Hangzhou, China.10.1109/ISCID.2015.143 ↗
20. Theoretical analysis of in-flatable beams made from orthotropic fabric10.1016/j.tws.2009.06.003 ↗
21. Zhou, S., Chen, J., and Wen, Q. (2019, January 8). A weight-based optimization algorithm of histogram equalization. Proceedings of the SPIE 10843, 9th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Sensing and Imaging, 108430T, Chengdu, China.
22. He, Y.-X. (2021, January 12–14). The Influence of Image Enhancement Algorithm on Face Recognition System. Proceedings of the 2021 2nd International Conference on Computer Engineering and Intelligent Control (ICCEIC), Chongqing, China.10.1109/ICCEIC54227.2021.00012 ↗
23. Identifying License Plates in Distorted Vehicle Images: Detecting Distorted Vehicle Licence Plates Using a Novel Preprocessing Methods With Hybrid Feature Descriptors10.1109/MITS.2022.3210226 ↗
24. Alimagadov, K.A., and Umnyashkin, S.V. (2021, January 26–29). Application of Wiener Filter to Suppress White Noise in Images: Wavelet vs Fourier Basis. Proceedings of the 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus), St. Petersburg, Moscow, Russia.10.1109/ElConRus51938.2021.9396470 ↗
25. Liu, S., Chai, Y., Yuan, R., and Miao, H. (2023). Laser 3D Tightly Coupled Mapping Method Based on Visual Information. Ind. Robot. Int. J. Robot. Res. Appl., 7–25.10.1108/IR-02-2023-0016 ↗
26. An improved LDR image enhancement algorithm based on visual characteristics and qray scale compensation
27. Design and modelling of a variable stiffness manipulator for surgical robots10.1016/j.mechatronics.2018.05.012 ↗