Autonomous Vehicle Camera Calibration Using Motion-Based Validation
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Solution Overview
Problem
Existing autonomous vehicle sensor calibration systems require specialized facilities and manual expertise, leading to high costs and inefficiencies, and recalibration is often necessary due to misalignment caused by environmental factors, which can affect sensor reliability and navigation accuracy.
Innovation Solution
A method for validating and recalibrating vehicle sensors using a calibration target that can be positioned relative to the vehicle, allowing for real-time calibration and validation without specialized facilities, using fiducials and tags to ensure accurate calibration even with partial visibility, and combining camera-based and motion-based validation factors to generate a confidence score.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration facilities with turntables and predefined positions are used, then sensor calibration accuracy is improved, but system complexity and cost increase
Solution Approach 1:
The patent extracts the essential calibration function from complex facilities by using a portable calibration target that can be positioned anywhere in the vehicle's field of view, eliminating the need for turntables and specialized installation infrastructure while maintaining calibration accuracy
Solution Approach 2:
The calibration target is designed to be universally applicable to multiple sensor types (cameras, LIDAR, radar) and can be used in various positions and orientations, replacing specialized facilities that were required for each specific calibration scenario
2Measurement precision
If traditional calibration facilities with precise positioning requirements are used, then calibration accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The calibration system becomes dynamic by allowing the calibration target to be positioned anywhere within the sensor's field of view rather than requiring fixed predefined positions, and the sensor can move relative to the target during calibration, making the process adaptable and easier to operate
Solution Approach 2:
The system performs self-calibration by using the vehicle's own motion and sensor data to automatically determine calibration parameters, eliminating the need for operators to manually position targets with high precision or possess specialized expertise in robotics and mathematics
3Reliability
If sensors are recalibrated frequently to maintain alignment, then reliability is improved, but loss of time increases
Solution Approach 1:
The calibration process can be performed continuously or periodically during vehicle operation without requiring the vehicle to be taken out of service, maintaining sensor reliability while minimizing disruption to vehicle utilization
Solution Approach 2:
The system performs preliminary calibration checks and adjustments during routine operations or maintenance intervals before misalignment becomes critical, preventing the need for extensive recalibration later and reducing overall downtime
Data Source
AI summary
Methods and systems for determining whether a camera of an autonomous vehicle (AV) is calibrated are disclosed. The method includes determining a relative positional range for a calibration target with respect to the AV, capturing a plurality of images of the calibration target, using the camera when the calibration target and the AV are positioned within the relative positional range, measuring a camera-based calibration factor and a motion-based validation factor based on the plurality of images for generating a confidence score, and generating a signal indicating that the camera is not calibrated when the confidence score is below a threshold.