Lidar Positioning System for Underground Mining
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Solution Overview
Problem
Lidar positioning systems in underground mining environments face challenges in accurately determining machine location due to non-unique shapes, computational intensity, and dynamic objects not accounted for in pre-existing maps, leading to potential loss of tracking and requiring manual intervention.
Innovation Solution
A positioning system that uses a Lidar unit to collect data on distances to reflective points in the worksite, comparing this data with reference data from known landmarks, and employing a controller to determine the machine's position based on predefined conditions, with the option to re-seed the system using distinctive landmarks for initial positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Lidar systems compare captured data with pre-existing maps to determine machine location, then positioning functionality is achieved, but computational intensity increases and processing speed decreases
Solution Approach 1:
The patent divides the worksite into multiple zones with predetermined reference positions distributed throughout. Instead of comparing Lidar data with the entire worksite map, the system segments the comparison process by only matching data against references within the current zone, significantly reducing computational load while maintaining positioning accuracy.
Solution Approach 2:
The system performs preliminary actions by pre-establishing multiple reference positions and their corresponding Lidar survey data before operation. These reference positions are predetermined and stored in the controller, allowing for rapid comparison and positioning without real-time computational intensity.
2Reliability
If Lidar systems rely solely on correlating captured data with mapped references, then positioning is achieved in familiar areas, but the system loses track when encountering non-unique shapes or dynamic objects not in the map
Solution Approach 1:
The system continuously compares current Lidar survey data with reference data from multiple predetermined positions and uses feedback from these comparisons to maintain positioning. When the machine moves to a new zone, the system receives feedback from the matching process and updates the position accordingly, allowing continuous tracking even in dynamic environments.
Solution Approach 2:
The positioning system is designed to handle multiple scenarios universally - it can position the machine using pre-existing map references in familiar areas, and when encountering non-unique shapes or dynamic objects, it can re-seed by matching against alternative reference positions. This multi-functional approach maintains reliability across varying conditions.
3Measurement precision
If multiple reference positions are established throughout the worksite, then positioning accuracy improves and re-seeding becomes possible, but system complexity increases
Solution Approach 1:
The system segments the worksite into zones with multiple reference positions, where each reference position contains Lidar survey data from predetermined locations. This segmentation allows the controller to select and compare against only relevant references in the current zone, improving precision while managing complexity through organized data structure.
4Measurement precision
If the Lidar system performs comprehensive data comparison to ensure accurate positioning, then measurement accuracy improves, but time consumption increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing multiple reference positions and their corresponding Lidar survey data before operation. These reference positions are predetermined and stored in the controller, allowing for rapid comparison and positioning without real-time computational intensity.
Solution Approach 2:
The patent divides the worksite into multiple zones with predetermined reference positions distributed throughout. Instead of comparing Lidar data with the entire worksite map, the system segments the comparison process by only matching data against references within the current zone, significantly reducing computational load while maintaining positioning accuracy.
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
Enhances the accuracy and efficiency of machine positioning in underground environments by reducing computational demands and minimizing manual intervention, maintaining reliable tracking even with dynamic objects and non-unique shapes.
Implementation Method 1
Lidar (Light Detection and Ranging; also referred to as light radar) positioning systems may be used to track the location of a machine
Implementation Method 2
The input data is associated with distances between the Lidar unit and respective light-reflective points in the worksite
Data Source
AI summary
A method for determining a position of a machine is disclosed. The method may include determining, using a Lidar unit on the machine, input data associated with distances between the Lidar unit and respective light-reflective points in the worksite. The method may also include comparing the input data with comparison data. The comparison data may have reference data sets indicative of distances between reference positions and the respective light-reflective points in the worksite. The reference positions may have a fixed location in the worksite. The method may further include determining the position of the machine as the reference position corresponding to a reference data set that correlates with the input data set.