Underground Mining Navigation Using Rock Bolt Point-Cloud Alignment
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Solution Overview
Problem
Existing navigation systems for underground mining machines face challenges due to the lack of satellite reception and significant noise in point cloud measurements, making it difficult to accurately register and extract three-dimensional features for robust navigation in uniform environments.
Innovation Solution
A navigation method that extracts stationary rock bolt features as point objects, forming constellations to determine the movement of the mining machine by aligning shapes defined by these points, using a laser range finder to capture 3D point clouds and a processor to determine relative location information based on these alignments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional 3D feature extraction methods are used in uniform underground environments, then navigation algorithms can be applied, but the measurement precision deteriorates due to noise in point cloud measurements and lack of distinct features
Solution Approach 1:
The patent extracts only the essential information needed for navigation by representing rock bolts as point features rather than full 3D objects. This extraction of key geometric elements (points defining shapes) from the noisy point cloud enables robust navigation by focusing on stable, repeatable features while filtering out unnecessary complexity and noise.
Solution Approach 2:
The patent transforms the representation of rock bolts from complex 3D objects to simple point features with specific geometric parameters. By changing the parameter representation (from full 3D geometry to point coordinates defining shapes like triangles), the system achieves computational efficiency and noise robustness while maintaining navigation accuracy.
2Reliability
If complex 3D object extraction methods are used to identify rock bolts, then more robust navigation can be achieved, but the computational complexity increases
Solution Approach 1:
The patent segments the rock bolt identification process into distinct stages: detecting apex shapes in point clouds, extracting point features, forming shapes from point combinations, and matching shapes between overlapping point clouds. This segmentation enables systematic processing that is both robust and computationally manageable.
Solution Approach 2:
The patent creates simplified geometric copies (shapes defined by point combinations) of the rock bolt configurations in the environment. These shape representations serve as computationally efficient proxies for the actual rock bolt positions, enabling robust matching and navigation calculations without requiring complex 3D object processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method is robust to noise and computationally efficient, providing accurate navigation by aligning shapes formed by rock bolt candidates, enhancing the precision of underground mining machine positioning.
Implementation Method 1
Laser range finders provide point clouds that could be used for navigation
Implementation Method 2
Laser range finder to capture 3D point clouds
Data Source
AI summary
This disclosure relates to navigation of an underground mining machine. A laser range finder captures first and second 3D point clouds of first and second overlapping parts of the underground mine from first and second positions of the mining machine respectively. A processor determines a first set of candidates for rock bolts as point feature objects from the first 3D point cloud; determines a second set of candidates for rock bolts as point feature objects from the second 3D point cloud; determines an alignment between first shapes defined by at least two of the first set of candidates for rock bolts and second shapes defined by at least two of the second set of candidates for rock bolts; and determines relative location information between the first position of the mining machine and the second position of the mining machine based on the alignment.