Vision and Inertial Navigation Combined-Based Pose Measurement Method of Cantilever Roadheader

Jicheng Wan, Xuhui Zhang (), Chao Zhang, Wenjuan Yang, Mengyu Lei, Yuyang Du and Zheng Dong
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Jicheng Wan: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Xuhui Zhang: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Chao Zhang: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Wenjuan Yang: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Mengyu Lei: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Yuyang Du: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Zheng Dong: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China

Sustainability, 2023, vol. 15, issue 5, 1-16

Abstract: Pose measurement of coal mine excavation equipment is an important part of roadway excavation. However, in the underground mining roadway of coal mine, there are some influencing factors such as low illumination, high dust and interference from multiple equipment, which lead to the difficulty in the position and pose measurement of roadheader with low measurement accuracy and poor stability. A combination positioning method based on machine vision and optical fiber inertial navigation is proposed to realize the position and pose measurement of roadheader and improve the accuracy and stability of the position and pose measurement. The visual measurement model of arm roadheader is established, and the optical fiber inertial navigation technology and the spatial coordinate transformation method are used. Finally, the Kalman filter fusion algorithm is used to fuse the two kinds of data to get the accurate roadheader pose data, and the inertia is compensated and corrected. Underground coal mine experiments are designed to verify the performance of the proposed method. The results show that the positioning error of the roadheader body using this method is within 40 mm, which meets the positioning accuracy requirements of roadway construction. This method compensates for the shortcomings of low accuracy and poor reliability of single vision measurement, single inertial navigation measurement and single odometer measurement.

Keywords: cantilever roadheader; visual measurement; optical fiber inertial navigation; Kalman filtering; combined positioning method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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