Underground Tunnel Floor Model Extraction for Route Planning
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Solution Overview
Problem
In complex underground environments like mines, using full 3D models for route calculation and location tracking is resource-intensive and inefficient, as it includes unnecessary data from walls and ceilings, which are not crucial for mobile object movement.
Innovation Solution
A method to generate a simplified floor model by identifying and extracting floor points from a 3D model based on surface normal directions and probability indicators, reducing the dataset to a 2D representation of the tunnel floor for use in route planning and positioning systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full 3D models are used for route calculation and location tracking, then comprehensive environmental data is available, but computational resources are excessively consumed and processing efficiency decreases
Solution Approach 1:
The patent extracts only the floor surface points from the complete 3D point cloud model by analyzing surface normals and identifying points with vertical orientations. This extraction removes unnecessary wall and ceiling data while retaining the essential floor information needed for mobile object positioning and route planning, thereby reducing computational load while maintaining necessary environmental awareness.
Solution Approach 2:
The patent segments the 3D point cloud data by categorizing points based on their surface normal directions. Floor points are separated from wall and ceiling points through geometric analysis, creating a segmented representation that focuses computational resources only on the relevant floor surface for navigation purposes.
2Loss of information
If full 3D models are used for route calculation and location tracking, then complete environmental representation is achieved, but data processing time and computational complexity increase
Solution Approach 1:
The patent extracts only the floor surface points from the complete 3D point cloud model by analyzing surface normals and identifying points with vertical orientations. This extraction removes unnecessary wall and ceiling data while retaining the essential floor information needed for mobile object positioning and route planning, thereby reducing computational load while maintaining necessary environmental awareness.
Solution Approach 2:
The patent applies partial action by processing only the necessary subset of point cloud data (floor points) rather than the complete 3D model. This selective processing approach reduces data processing time while maintaining sufficient environmental representation for navigation tasks, avoiding the excessive computation of irrelevant surface data.
3Productivity
If simplified floor models are generated by extracting floor points, then computational efficiency is improved, but accuracy of surface representation may be reduced
Solution Approach 1:
The patent applies local quality by differentiating between floor points and non-floor points based on surface normal analysis. Each point in the point cloud is evaluated individually, and floor points are identified with high precision using geometric criteria (vertical surface normals). This ensures that the simplified floor model maintains accurate representation of the actual floor surface geometry while excluding irrelevant structures.
Solution Approach 2:
The patent changes the parameter used for point selection from arbitrary or uniform sampling to surface normal direction analysis. By using the vertical orientation of floor surfaces as the selection criterion, the method accurately distinguishes floor points from wall and ceiling points, preserving the geometric fidelity of the floor model while simplifying the overall data structure.
Data Source
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AI summary
According to an example aspect of the present invention, there is provided a method, comprising: receiving a three-dimensional model of an underground tunnel, identifying floor points among points of the three-dimensional model; extracting the floor points, and applying at least a part of the extracted floor points as a floor model of the tunnel for positioning or route planning of a mobile object in the underground tunnel.