Online Sensor Calibration Verification for Autonomous Vehicles
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Solution Overview
Problem
Autonomous vehicles face challenges in maintaining accurate sensor calibration, leading to incorrect world model generation due to sensor perturbations, as existing systems rely on unreliable extrinsic calibration parameters.
Innovation Solution
An online sensor calibration verification system that continuously monitors and verifies the positional relationship between extracted calibration features and a static reference model, using detectible fiduciary marks or surface features to determine sensor faults and calibration status, ensuring only calibrated data is incorporated into the world model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of stationary object
If extrinsic calibration parameters are used for sensor integration, then the system can operate without frequent recalibration, but the calibration accuracy deteriorates over time due to sensor perturbations
Solution Approach 1:
The system continuously monitors the positional relationship between extracted calibration features and the static reference feature model, comparing actual sensor measurements against expected values to detect calibration drift and trigger verification processes
Solution Approach 2:
The system performs preliminary calibration verification by extracting calibration features and comparing them against a pre-established static reference feature model before incorporating sensor data into the world model, preventing accumulation of calibration errors
2Measurement precision
If sensor measurements are continuously incorporated into the world model, then the navigation accuracy is improved, but incorrect measurements from uncalibrated sensors corrupt the world model
Solution Approach 1:
The calibration verification module provides continuous feedback on sensor calibration status by comparing extracted calibration features against the reference model, enabling the system to detect when sensors have drifted from their calibrated state
Solution Approach 2:
The electronic calibration verification module acts as an intermediary between the sensor and the world model unit, filtering and verifying sensor measurements before they are incorporated into the world model, preventing corrupted data from degrading navigation accuracy
3Measurement precision
If online calibration verification is implemented, then sensor calibration accuracy is maintained, but the system complexity increases
Solution Approach 1:
The system performs self-verification of calibration by using its own sensors to extract and analyze calibration features from the static reference feature model, eliminating the need for external calibration equipment or manual intervention
Solution Approach 2:
The calibration verification system uses the same sensors and processing algorithms already present in the autonomous vehicle for navigation, allowing the verification function to leverage existing system resources rather than requiring entirely separate dedicated hardware
Data Source
AI summary
An online sensor calibration verification system includes at least one sensor configured to extract a calibration feature included in a field of view of the sensor. The online sensor calibration verification system further includes an electronic calibration verification module configured to determine a static reference feature model, and to verify a calibration of the at least one sensor based on a positional relationship between an extracted calibration feature and the static reference feature model.