LiDAR Camera Calibration via Combined Image Alignment
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Solution Overview
Problem
Calibrating cameras and LiDAR sensors in vehicles is a tedious process, often requiring factory-level precision and lacks user-friendly methods for fine-tuning, which can lead to suboptimal data fusion and object detection accuracy.
Innovation Solution
A system and method that combines camera images and three-dimensional point cloud images from LiDAR sensors, allowing users to adjust calibration parameters through a user interface, enabling fine-tuning of camera and LiDAR sensor alignment by displaying a combined image and allowing users to move and align image components to match, thereby adjusting calibration parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If calibration is performed using a known target like a checkerboard, then manufacturing precision is improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The system uses naturally occurring objects with edges in the environment as calibration targets, eliminating the need for specialized calibration equipment like checkerboards. The camera and LiDAR sensor automatically detect and use these environmental features for calibration, making the process self-service and eliminating manual setup requirements.
Solution Approach 2:
The system introduces a processing system that acts as an intermediary between the sensors and calibration targets. This intermediary automatically identifies objects with edges in the environment, extracts calibration data from them, and adjusts sensor parameters, mediating the calibration process between the sensors and environmental features.
2Manufacturing precision
If calibration is performed at the factory, then manufacturing precision is improved, but adaptability deteriorates
Solution Approach 1:
The calibration parameters are made dynamic and adjustable after manufacturing. The system allows calibration parameters to be modified in real-time based on environmental conditions and operational requirements, transitioning from static factory calibration to dynamic field calibration that adapts to changing conditions.
Solution Approach 2:
The system enables changes in calibration parameters based on detected environmental features. By continuously analyzing objects with edges in the environment and adjusting calibration parameters accordingly, the system adapts to different operational contexts and environmental conditions after manufacturing.
3Ease of operation
If automated calibration is used without targets, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The system focuses calibration on specific local features - objects with distinct edges in the environment. By identifying and using these particular local features rather than requiring comprehensive target coverage, the system achieves precise calibration through targeted feature detection and utilization.
Solution Approach 2:
The system replaces mechanical alignment procedures with automated image and point cloud processing. Instead of physically aligning sensors using mechanical methods and visual inspection, the system uses computational algorithms to process camera images and LiDAR point clouds, automatically determining calibration parameters through digital analysis.
Data Source
AI summary
A system for calibrating at least one camera and a light detection and ranging (“LiDAR”) sensor includes one or more processors and a memory in communication with the one or more processors that stores an initial calibration module and a user calibration module. The initial calibration module includes instructions that cause the one or more processors to obtain a camera image from the at least one camera, determine when the camera image includes at least one object having at least one edge, obtain a three-dimensional point cloud image from the LiDAR sensor that includes the at least one object having at least one edge and generate a combined image, that includes at least portions of the camera image and at least portions of the three-dimensional point cloud image. The user calibration module includes instructions that cause the one or more processors to display the combined image on a display, receive at least one input from a user interface, and adjust a calibration parameter of at least one of the LiDAR sensor and the at least one camera in response to the one or more inputs from the user interface.