Polyhedral Calibration Target for Camera-LiDAR Sensor Alignment
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately calibrating sensors due to manufacturing defects and environmental factors, leading to inconsistent data interpretation and potential safety risks, as existing calibration methods do not effectively account for intrinsic sensor properties and extrinsic relationships between sensors.
Innovation Solution
A polyhedral sensor calibration target is used, which includes multiple surfaces with visual markings, allowing for simultaneous calibration of multiple sensor types like cameras and LIDAR sensors through intrinsic and extrinsic calibration processes, improving the accuracy and consistency of sensor data by mapping vertices and surfaces in a three-dimensional environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple separate calibration targets are used for different sensor types, then each sensor can be calibrated independently, but the calibration process becomes time-consuming and space-intensive
Solution Approach 1:
The patent combines multiple calibration targets for different sensor types (camera, LIDAR, radar) into a single polyhedral calibration target. This merged target contains multiple surfaces with different visual markings that can simultaneously calibrate multiple sensor types, eliminating the need for separate calibration processes and significantly reducing calibration time while maintaining accuracy for each sensor type
Solution Approach 2:
The polyhedral calibration target is designed with multi-functionality to serve multiple calibration purposes. Each surface of the polyhedron contains specific visual markings tailored for different sensor types, allowing a single target to perform intrinsic calibration for cameras, extrinsic calibration for LIDAR, and calibration for radar sensors simultaneously, making the calibration system universal and efficient
2Measurement precision
If multiple separate calibration targets are used for different sensor types, then each sensor can be calibrated independently, but the space required for calibration increases
Solution Approach 1:
The patent merges multiple calibration targets into a single polyhedral structure that consolidates all calibration functions into one compact object. This eliminates the need for multiple separate calibration targets occupying different spaces, reducing the overall calibration area required while maintaining the ability to calibrate multiple sensor types accurately
Solution Approach 2:
The patent transitions from two-dimensional planar calibration targets to a three-dimensional polyhedral calibration target. This dimensional change allows multiple calibration surfaces to be stacked and oriented in different directions within a compact volume, maximizing the calibration functionality within a minimal space footprint and enabling simultaneous access to multiple calibration surfaces
3Productivity
If a polyhedral calibration target with multiple surfaces is used, then calibration accuracy and efficiency improve, but the device complexity increases
Solution Approach 1:
The polyhedral calibration target is segmented into multiple surfaces, each independently designed with specific visual markings for different sensor types. This segmentation allows each surface to be optimized for its specific calibration function while maintaining a relatively simple overall polyhedral structure, balancing complexity with functionality and enabling efficient multi-sensor calibration
Data Source
AI summary
A polyhedral sensor target includes multiple surfaces. A housing, such as a vehicle, may include a camera and a distance measurement sensor, such as a light detection and ranging (LIDAR) sensor. The housing may move between different positions during calibration, for instance by being rotated atop a turntable. The camera and distance measurement sensor may both capture data during calibration, from which visual and distance measurement representations of the polyhedral sensor target are identified. The camera and distance measurement sensor are calibrated based on their respective representations, for example by mapping vertices within the representations to the same location.