Stereo Camera Calibration Using Radar and LiDAR Disparity Feedback
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Solution Overview
Problem
Autonomous vehicle cameras in stereoscopic configurations face calibration challenges due to movement and misalignment, leading to inaccurate distance calculations and potential safety issues during autonomous driving.
Innovation Solution
Dynamic calibration of cameras using input from other sensors like radar or LiDAR, where disparity between camera images is calculated and adjusted to align with sensor data, ensuring accurate stereoscopic camera functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cameras are fixed in stereoscopic configuration, then initial calibration is simple, but calibration accuracy deteriorates due to movement and misalignment during operation
Solution Approach 1:
The patent implements dynamic calibration by allowing the camera system to self-adjust during operation. The calibration process is no longer static but continuously adapts to changes in camera positioning and alignment, transforming the system from a fixed calibration state to a dynamic self-correcting state that maintains accuracy despite physical movements.
Solution Approach 2:
The system uses feedback from detected objects and their spatial relationships to continuously monitor and adjust camera calibration. By comparing expected object positions with actual detected positions, the system generates corrective feedback signals that realign the stereoscopic camera configuration, ensuring sustained measurement precision.
2Measurement precision
If dynamic calibration using other sensors is implemented, then calibration accuracy is maintained, but system complexity increases
Solution Approach 1:
The patent merges multiple sensor types (stereoscopic cameras, radar, LiDAR, ultrasonic sensors) into a unified calibration system. By combining the strengths of different sensors—visual data from cameras and direct distance measurements from radar/LiDAR—the system achieves accurate calibration while distributing the computational workload across multiple sensor inputs.
Solution Approach 2:
The calibration system is designed to be universal by accepting input from multiple sensor types and adapting the calibration process based on which sensors are available. This multi-functional approach allows the same calibration framework to work with different sensor configurations, reducing overall system complexity despite the variety of sensors involved.
3Measurement precision
If frequent recalibration is performed, then distance reading accuracy is maintained, but processing time and computational load increase
Solution Approach 1:
The system performs calibration periodically rather than continuously, triggered by specific events such as detection of calibration objects, changes in vehicle motion state, or predetermined time intervals. This periodic approach maintains accuracy when needed while minimizing unnecessary processing during stable operating conditions.
Solution Approach 2:
The calibration system operates autonomously by automatically detecting when calibration is needed and performing adjustments without external intervention. The system monitors its own calibration status using detected objects and sensor data, initiating recalibration only when degradation is detected, thereby reducing overall processing time and computational burden.
Data Source
AI summary
Dynamic calibration of cameras in a stereoscopic configuration may include: determining a disparity between first image data from a first camera and second image data from a second camera, wherein the first camera and the second camera are in a stereoscopic configuration, and wherein the disparity comprises a difference in placement of one or more objects in the first image data relative to the second image data; and adjusting one or more of the first camera or the second camera, based on the disparity and sensor data from a sensor other than the first camera and the second camera, to calibrate the stereoscopic configuration of the first camera and the second camera to achieve stereoscopic camera distance functionality.