Multi-Sensor Extrinsic Calibration via 3D Target Stacking
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Solution Overview
Problem
Current extrinsic sensor calibration methods for vehicles require large calibration spaces and different setups for various sensor combinations, making them inefficient and impractical for real-world applications.
Innovation Solution
The development of mobile and stationary calibration stations that use calibration targets to perform extrinsic calibration of LiDAR, camera, and RADAR sensors without the need for precise global coordinate system alignment, allowing for a unified calibration method across different sensor combinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional extrinsic sensor calibration methods are used, then sensor calibration accuracy is improved, but calibration space requirements increase significantly
Solution Approach 1:
The patent transitions from 2D planar calibration targets to 3D multi-layer calibration targets with vertical stacking. The calibration target includes multiple calibration planes arranged in different spatial layers, enabling sensors to be calibrated in three-dimensional space rather than requiring large horizontal areas. This dimensional change allows accurate extrinsic calibration while significantly reducing the physical calibration space needed.
Solution Approach 2:
The patent implements a nested structure where multiple calibration planes are integrated within a compact vertical arrangement. The calibration target comprises first, second, and third calibration planes stacked in different layers, with each plane containing multiple calibration targets. This nesting approach consolidates what would traditionally require separate large-area setups into a single compact structure.
2Measurement precision
If separate extrinsic calibration setups are used for different sensor combinations, then calibration accuracy for each sensor pair is improved, but device complexity increases
Solution Approach 1:
The patent creates a universal calibration target that can simultaneously calibrate multiple sensor types including LiDAR, cameras, and RADAR. The calibration target incorporates features visible to different sensor modalities: reflective markers for optical sensors, retroreflective elements for LiDAR, and radio frequency reflective structures for RADAR. This single multi-functional target replaces the need for separate calibration setups for each sensor combination.
Solution Approach 2:
The patent merges multiple calibration functions into a single integrated calibration target structure. The calibration target combines calibration planes with different materials and geometric features that serve multiple sensor types simultaneously. By combining LiDAR calibration markers, camera calibration patterns, and RADAR calibration reflectors into one target assembly, the system eliminates the complexity of managing separate calibration setups for different sensor pairs.
3Measurement precision
If laser scanning methods are used for calibration, then transformation between reference point and sensor is obtained, but intrinsic parameter accuracy is not addressed
Solution Approach 1:
The patent performs intrinsic parameter calibration before extrinsic calibration in a predetermined sequence. The calibration process first determines intrinsic parameters of each sensor by having sensors observe the calibration target at multiple known positions and orientations. These intrinsic parameters are then used in subsequent extrinsic calibration to accurately determine transformation relationships. This preliminary action ensures that intrinsic parameter accuracy is established before computing extrinsic transformations.
Solution Approach 2:
The patent implements a feedback mechanism where the calibration system uses the observed calibration targets to iteratively refine both intrinsic and extrinsic parameters. Sensors capture images of the calibration target from multiple positions, and the system uses these observations to compute and update intrinsic parameters, then uses the refined intrinsic parameters to compute extrinsic transformations. This feedback loop ensures that both intrinsic and extrinsic calibrations are accurately determined rather than treating them as separate one-way processes.
Data Source
AI summary
A calibration system for multi-sensor extrinsic calibration in a vehicle includes one or more calibration targets provided around an external environment within a threshold distance of the vehicle. Each of the one or more calibration targets includes a combination of sensor targets configured to be measured by and used for calibrating a pair of sensors selected from the group consisting of a first sensor, a second sensor or a third sensor. The system also includes a vehicle placement section configured to accommodate the vehicle on the vehicle placement section for detection of the one or more calibration targets.