Dynamic Scene Calibration for Vehicle Sensor Alignment
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately calibrating sensors due to manufacturing discrepancies and environmental factors, leading to inconsistent data interpretation and potential safety risks.
Innovation Solution
A dynamic scene calibration system using a motorized turntable and sensor targets allows vehicles to perform intrinsic and extrinsic calibrations of sensors, ensuring accurate data capture and alignment across different vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If sensors are mounted on vehicles without calibration, then vehicle production and deployment is simplified, but sensor data accuracy and consistency deteriorates due to manufacturing defects and environmental factors
Solution Approach 1:
The patent applies preliminary action by performing sensor calibration before vehicles are deployed to collect real-world data. A controlled calibration environment with known geometric targets is used to pre-calibrate sensors, ensuring accuracy is established in advance. This resolves the contradiction by maintaining measurement precision through pre-calibration while allowing ease of manufacture during actual vehicle production, as the calibration process is standardized and automated.
Solution Approach 2:
The patent replaces manual mechanical calibration processes with automated computational methods. Instead of physically adjusting sensor mounting hardware to achieve alignment, the system uses computer vision algorithms and mathematical transformations to calculate and correct sensor parameters automatically. This substitution maintains measurement precision while eliminating complex mechanical adjustment procedures, preserving ease of manufacture.
2Measurement precision
If dynamic calibration environments with multiple targets are used, then calibration accuracy and consistency improve, but system complexity and calibration time increase
Solution Approach 1:
The patent applies segmentation by dividing the calibration environment into distinct, modular components: multiple calibration targets positioned at known locations, separate sensor mounting positions, and independent measurement sequences. This segmentation allows the complex calibration task to be broken into manageable segments that can be processed independently, reducing overall system complexity while maintaining high calibration accuracy through comprehensive multi-point measurement.
Solution Approach 2:
The patent uses copying by creating multiple identical calibration targets with precisely replicated geometric features at different known positions. These copies provide consistent reference data across multiple measurement points, enabling accurate calibration without requiring complex unique fixtures for each position. The replicated targets simplify the calibration system while maintaining high precision through redundant measurement opportunities.
3Reliability
If comprehensive sensor calibrations are performed for all vehicles, then data reliability improves, but calibration time and resource consumption increase
Solution Approach 1:
The patent applies self-service by enabling vehicles to perform their own calibration measurements automatically within the controlled environment. Each vehicle's sensors autonomously capture images of the calibration targets, and onboard or connected computing systems automatically process the data to determine calibration parameters. This self-service approach maintains high data reliability through comprehensive calibration while minimizing calibration time by eliminating manual intervention and streamlining the process.
Solution Approach 2:
The patent creates an inert calibration environment with controlled lighting, fixed target positions, and stable physical conditions that eliminate external variables. This controlled atmosphere ensures that calibration measurements are not affected by environmental fluctuations, maintaining high reliability. The standardized inert environment allows for rapid, repeatable calibration processes across all vehicles, reducing time loss while ensuring consistent high-quality results.
Data Source
AI summary
Sensors coupled to a vehicle are calibrated using a dynamic scene with sensor targets around a motorized turntable that rotates the vehicle to different orientations. The sensors capture data at each orientation along the rotation. The vehicle's computer identifies representations of the sensor targets within the data captured by the sensors, and calibrates the sensor based on these representations. The motorized turntable may confirm that rotation has stopped to the vehicle to trigger sensor capture, and the vehicle may communicate completion of sensor capture at an orientation to the motorized turntable to trigger further rotation.