LiDAR Self-Diagnostic Position and Orientation Calibration
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Solution Overview
Problem
Existing LiDAR systems require cumbersome and complex methods to diagnose abnormal changes in their relative position and orientation to an apparatus, which can lead to precision issues in surveying and mapping, potentially causing safety accidents in autonomous driving applications.
Innovation Solution
A diagnostic method for LiDAR that allows for automatic detection of abnormal changes in position and orientation without the need for other detector devices, using a calibration object to determine deviations by comparing reference and measurement data, and determining the deviation direction and magnitude based on point cloud characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the LiDAR uses existing diagnostic methods requiring cooperation with other detector apparatuses, then the position and orientation can be diagnosed, but the process becomes cumbersome and increases device complexity
Solution Approach 1:
The LiDAR system performs self-diagnosis by using its own point cloud data to detect position and orientation abnormalities. The system scans a calibration object and compares the obtained point cloud data with pre-stored reference data to automatically determine deviations, eliminating the need for external detector apparatuses and complex coordination processes.
Solution Approach 2:
The invention extracts the diagnostic function from the broader sensor system by utilizing only the LiDAR's own point cloud data and pre-stored reference data. This extraction allows the LiDAR to independently diagnose its position and orientation without requiring cameras or other detector devices, thereby simplifying the overall apparatus structure.
2Reliability
If the LiDAR uses existing diagnostic methods requiring point cloud data matching with images, then position and orientation can be diagnosed, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The invention extracts the diagnostic function from the broader sensor system by utilizing only the LiDAR's own point cloud data and pre-stored reference data. This extraction allows the LiDAR to independently diagnose its position and orientation without requiring cameras or other detector devices, thereby simplifying the overall apparatus structure.
Solution Approach 2:
The system performs preliminary action by pre-storing reference point cloud data obtained when the LiDAR is in a standard position and orientation. During operation, the system simply compares current point cloud data with this pre-stored reference data, eliminating the need for time-consuming image capture and matching processes.
3Reliability
If the LiDAR uses existing diagnostic methods requiring multiple detector apparatuses, then position and orientation can be diagnosed, but the structure complexity increases
Solution Approach 1:
The LiDAR system performs self-diagnosis by using its own point cloud data to detect position and orientation abnormalities. The system scans a calibration object and compares the obtained point cloud data with pre-stored reference data to automatically determine deviations, eliminating the need for external detector apparatuses and complex coordination processes.
Solution Approach 2:
The LiDAR system serves multiple functions: it performs normal detection operations and simultaneously performs self-diagnosis of position and orientation. By using the same point cloud scanning mechanism for both detection and diagnosis, the system avoids adding separate diagnostic apparatuses, thereby reducing overall structural complexity.
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 quick and accurate diagnosis of LiDAR position and orientation changes, ensuring safe operation of autonomous driving vehicles by simplifying the diagnostic process and improving precision.
Implementation Method 1
LiDAR is a commonly used detector device that uses a reflected echo from a target to determine information about the target
Data Source
AI summary
This disclosure provides a diagnostic method for a position and orientation of a LiDAR, where the LiDAR is fixed to an apparatus, the diagnostic method including: determining a first reference data of scanning a calibration object by the LiDAR when it is in a standard position and orientation; controlling the LiDAR to scan the calibration object in a current position and orientation and collect a first measurement data of the LiDAR; and determining, based on the first reference data and the first measurement data, whether the current position and orientation of the LiDAR deviates from the standard position and orientation. In embodiments of this disclosure, using the characteristics of point cloud data of the LiDAR, the LiDAR diagnoses by itself an abnormal change in its relative position and orientation to the apparatus during the normal operation without the cooperation of other detector devices. Calculations of the diagnostic method are simple, and results are accurate. Embodiments of this disclosure further provide a LiDAR and an autonomous driving vehicle. By using the aforementioned diagnostic method, the relative position and orientation of the LiDAR to the autonomous driving vehicle can be quickly and accurately diagnosed, which can ensure safe operation of the autonomous driving vehicle.