Lidar Decalibration Detection via Virtual Surface Interpolation
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Solution Overview
Problem
Current lidar systems in vehicles lack effective methods for in-operation decalibration detection, which is crucial for ensuring safe and reliable operation of automated or autonomous vehicles, particularly outside controlled environments like workshops.
Innovation Solution
A method and device utilizing multiple laser receiver systems to scan a shared viewing region, interpolating virtual measuring surfaces from point clouds reflected off a flat surface, and determining if these surfaces coincide or are bent, allowing for the recognition and potential recalibration of decalibration in lidar systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple laser receiver systems scan a shared viewing region to detect decalibration, then the reliability of lidar system operation is improved, but the device complexity increases
Solution Approach 1:
The patent applies multi-functionality by using multiple laser receiver systems that serve dual purposes: their primary function for environmental scanning and a secondary function for decalibration detection by scanning a shared viewing region and comparing measuring surfaces. This allows the same hardware to perform both navigation and self-diagnosis functions.
Solution Approach 2:
The lidar system performs self-diagnosis by using its own laser receiver systems to scan a flat surface in the shared viewing region, generate point clouds, and automatically detect decalibration conditions through surface comparison. The system monitors its own calibration status without requiring external calibration equipment or manual intervention.
2Measurement precision
If measuring surfaces are interpolated and compared to detect decalibration, then the measurement precision is improved, but the loss of time increases
Solution Approach 1:
The patent applies preliminary action by pre-defining the flat surface in the shared viewing region that will serve as the reference target for decalibration detection. The surface is predetermined with specific geometric properties (flatness, size, position) that optimize the calibration check process, allowing rapid comparison without complex real-time analysis.
Solution Approach 2:
The patent uses parameter changes by interpolating point clouds into continuous measuring surfaces using mathematical models (B-spline or Bezier surfaces). This transformation converts discrete point data into smooth surfaces that can be efficiently compared, changing the data representation parameters to facilitate faster and more precise decalibration detection.
3Productivity
If automatic decalibration recognition is implemented during normal operation, then the productivity is improved, but the ease of operation decreases
Solution Approach 1:
The patent implements feedback by continuously monitoring the coincidence of measuring surfaces from multiple laser receiver systems and automatically detecting decalibration conditions. The system provides real-time feedback on calibration status and can trigger alerts or initiate recalibration procedures, enabling proactive maintenance without interrupting vehicle operation.
Solution Approach 2:
The patent replaces manual calibration checks with an automated optical and computational system. Instead of requiring physical inspection or manual measurement tools, the system uses laser scanning, point cloud processing, and surface interpolation algorithms to automatically detect decalibration, substituting mechanical procedures with automated digital processes.
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
Enables automatic decalibration recognition and recalibration of lidar systems during normal vehicle operation, reducing maintenance needs and ensuring safe operation within predetermined parameter limits, thereby minimizing downtime and user inconvenience.
Implementation Method 1
Point clouds are identified that are created by the reflection of a respective laser beam of the laser receiver systems on the flat surface
Data Source
AI summary
A method for recognizing a decalibration of a lidar system includes scanning an environment by the lidar system with laser receiver systems in a shared viewing region. A flat surface located in the shared viewing region is scanned with the laser receiver systems. Point clouds are identified that are created by a reflection of a respective laser beam of the laser receiver systems on the flat surface. A virtual measuring surface is interpolated by the identified point cloud of the respective laser beam. It is determined whether the virtual measuring surfaces for the respective laser beams substantially coincide with one another and/or are bent. A decalibration of the lidar system is deduced when it is determined that the virtual measuring surfaces for the respective laser beams do not substantially coincide with one another and/or that at least one of the virtual measuring surfaces for the respective laser beams is bent.