Mobile Vehicle LiDAR Calibration Using Odometer Pose Data
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Solution Overview
Problem
Smart mobile vehicles deviate from set routes due to component deviations and mechanical fatigue, requiring cumbersome manual calibration that relies heavily on human skill and experience.
Innovation Solution
An automatic calibration method using an odometer and lidar module to generate datasets for calibrating coordinate and angle parameters, employing point-cloud registration and regression models to adjust parameters for precise alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration is performed, then calibration accuracy can be achieved, but calibration time is long (half an hour to one and a half hours) and depends heavily on operator skill
Solution Approach 1:
The patent replaces manual mechanical calibration operations with an automated system using odometer and lidar modules. The control module automatically processes movement datasets and distance datasets through point-cloud registration algorithms to generate calibrated parameter sets, eliminating dependence on operator skill and significantly reducing calibration time while maintaining accuracy.
Solution Approach 2:
The mobile vehicle performs self-calibration by autonomously collecting its own movement data via odometer and environmental distance data via lidar. The control module processes these self-collected datasets to automatically generate calibration parameters without requiring external manual intervention, enabling the system to calibrate itself efficiently.
2Ease of manufacture
If manual calibration is performed, then calibration can be completed, but the process is cumbersome and requires high operator skill and experience
Solution Approach 1:
The patent replaces complex manual calibration procedures with an automated computational system. The control module executes point-cloud registration algorithms that automatically process odometer movement datasets and lidar distance datasets, generating calibrated coordinate and angle parameter sets without requiring operator expertise in calibration techniques.
Solution Approach 2:
The patent introduces datasets as intermediary elements between the physical calibration process and the control system. The odometer generates movement datasets and the lidar generates distance datasets, which serve as intermediate representations that the control module processes through algorithms to produce final calibration parameters, simplifying the overall calibration workflow.
Data Source
AI summary
A method for calibrating a mobile vehicle includes the following. The mobile vehicle performs a calibrating process, during which an odometer module of the mobile vehicle obtains a movement dataset related to movements of the mobile vehicle, and a lidar module of the mobile vehicle obtains a distance dataset related to distances to surroundings detected by the lidar module. A control module generates a variation dataset based on the movement dataset, where the variation dataset is related to changes in pose of the lidar module during the calibrating process. The control module generates a calibrated coordinate parameter and a calibrated angle parameter based on the variation dataset and the distance dataset, where the calibrated coordinate parameter is related to a position of the lidar module on the mobile vehicle, and where the calibrated angle parameter is related to an angle of the lidar module relative to the mobile vehicle.