Laser Scanner Signal Timing for Transparent and Mirroring Surface Detection
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Solution Overview
Problem
Laser scanners struggle to accurately identify and differentiate transparent and reflective/mirroring surfaces, leading to false measurements and manual post-processing to correct these errors, which is inefficient and computationally intensive.
Innovation Solution
A method for identifying transparent and mirroring plane candidates by analyzing the time characteristics of reception signals from laser scanner pulses, recognizing circular accumulation patterns, and assigning spatial and intensity information to determine the presence of these surfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual curating of false measured points is performed, then measurement accuracy is improved, but productivity deteriorates due to time-consuming manual process
Solution Approach 1:
The system automatically identifies and removes false measured points through computational algorithms that analyze point cloud characteristics, temporal patterns, and spatial relationships. The laser scanning system performs self-correction by detecting and filtering out erroneous measurements without requiring manual intervention, thereby maintaining high measurement accuracy while significantly improving processing efficiency.
2Measurement precision
If sophisticated post processing algorithms are used to remove false measured points, then measurement accuracy is improved, but device complexity and computational resources required increase
Solution Approach 1:
The post-processing algorithm is divided into multiple independent modules: false point detection module, classification module, and removal module. Each module handles specific aspects of false measurement identification through targeted computational operations, reducing the complexity burden on any single algorithm while maintaining comprehensive accuracy improvement.
3Adaptability or versatility
If laser scanner measures transparent and reflective surfaces, then complete environmental digitization is achieved, but measurement reliability deteriorates due to false distance measurements
Solution Approach 1:
The system continuously monitors measurement quality by analyzing the temporal characteristics of return signals and comparing expected versus actual distance measurements. When false measurements are detected through pattern recognition and consistency checking, the system provides feedback to filter out erroneous data points, thereby maintaining measurement reliability while preserving complete environmental digitization capability.
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
Automatically identifies transparent and mirroring surfaces, improving collision avoidance and digitization accuracy in environments with glass and reflective surfaces, and enabling efficient removal of false measurements.
Implementation Method 1
a laser scanner emitting distance measuring light pulses
Implementation Method 2
detecting backscattered portions of the emitted distance measuring light pulse
Implementation Method 3
recording, for an, in particular for each, emitted distance measuring light pulse, a time characteristic of a reception signal
Data Source
AI summary
The invention relates to a computer implemented method for identifying transparent and/or mirroring plane candidates from measurement data resulting from scanning an environment by a laser scanner emitting distance measuring light pulses.