Abstract

The efficiency of automatic underground tunneling is significantly depends on the localization accuracy and reliable for the Boom-type roadheader. In comparison with other underground equipment positioning methods, vision-based measurement has gained attention for its advantages of non-contact and no accumulated error. However, the harsh underground environment, especially the geometric errors brought by the vibration of the machine body to the underground camera model, has a certain influence on the accuracy and stability for the vision-based underground localization. In this paper, a laser beams-based localization methods for the machine body of Boom-type roadheader is presented, which can tackle the dense-dust, low illumination environment with the stray lights interference. Taking mining vibration into consideration, an underground camera non-uniform blur model that incorporate the two-layer glasses refraction effect was established to eliminate vibration errors. The blur model explicitly reveals the change of imaging optical path under the influence of vibration and double layer explosion-proof glass. On the basis of this, the underground laser beams extraction and positioning are presents, which is with well environmental adaptability, and the improved 2P3L (two-points-three-lines) localization model from line correspondences are developed. Experimental evaluation are designed to verify the performance of the proposed method, and the deblurring algorithm is investigated and evaluated. The results show that the proposed methods is effective to restore the blurred laser beams image that caused by the vibration, and can meet the precision need of roadheader body localization for roadway construction in coal mine.

Highlights

  • The intelligent localization of coal mine roadway tunneling is facing severe challenges

  • The experimental platforms were built to verify and evaluate the above theoretical research, which include the environmental adaptability of vision-based laser beams segmentation, extraction and positioning, the effectiveness of the proposed underground camera blur model and deblurring algorithms, and the performance of the proposed machine body localization method

  • This paper proposed a monocular vision-based measurement method for the machine body of Boom-type roadheader

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Summary

INTRODUCTION

The intelligent localization of coal mine roadway tunneling is facing severe challenges. Due to the motion and vibration of the Boom-type roadheader in coal mining, the pixel points in the laser beams image will continuously move across the image plane during exposure and form a blurred laser beams image This blurring effect increases feature location errors and degrades pose estimation accuracy. This paper proposes a novel laser beams-based machine body localization system for the Boom-type roadheader to improve the accuracy and reliability of the body positioning in tunneling face. With the Boom-type roadheader’s motion and vibration in coal mining, the relative pose between the underground camera and the laser beam-based target will changed.

UNDERGROUND CAMERA BLUR MODELING AND DEBLURING
LASER BEAMS SEGMENTATION AND POSITIONING
A22 B22 C22
A32 B32 C32
EVALUATION
ENVIRONMENTAL ADAPTABILITY EVALUATION
POSE ESTIMATION EVALUATION
VI.CONCLUSION
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