AR Vehicle Sensor Calibration System
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Solution Overview
Problem
The calibration of vehicle sensors is a time-consuming and error-prone process that relies on physical measuring guides and specific dimensions, which can lead to human errors during the placement of calibration reflectors.
Innovation Solution
A system using optical sensors and augmented reality to capture image data, determine the origin point, and retrieve calibration positions from a database, displaying the placement array of calibration locations in an augmented reality depiction to minimize human error and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional physical measuring guides and manual measurement methods are used for sensor calibration, then the calibration process can be completed with simple equipment, but the process becomes time-consuming and error-prone due to human measurement errors
Solution Approach 1:
The patent replaces manual mechanical measurement methods with an automated optical measurement system. A camera captures images of the vehicle and calibration targets, and image processing algorithms automatically calculate calibration parameters, eliminating the need for manual tape measurements and reducing both time and human error.
Solution Approach 2:
The patent uses visual markers and target objects that can be captured via image copying. The calibration targets are placed at specific locations, and their positions are determined through image capture and processing, creating a digital copy of the physical measurement process that is more accurate and efficient.
2Reliability
If manual measurement and placement methods are used, then the equipment required is simple and inexpensive, but human error increases during the calibration process
Solution Approach 1:
The patent replaces manual mechanical measurement methods with an automated optical measurement system. A camera captures images of the vehicle and calibration targets, and image processing algorithms automatically calculate calibration parameters, eliminating the need for manual tape measurements and reducing both time and human error.
Solution Approach 2:
The patent introduces visual markers and target objects as intermediaries between the physical vehicle and the digital measurement system. These markers serve as reliable reference points that can be accurately detected by the camera, ensuring consistent and repeatable measurements across different calibration sessions.
3Measurement precision
If automated optical measurement systems are used to improve calibration accuracy, then measurement precision increases, but the system complexity and initial cost increase
Solution Approach 1:
The patent replaces manual mechanical measurement methods with an automated optical measurement system. A camera captures images of the vehicle and calibration targets, and image processing algorithms automatically calculate calibration parameters, eliminating the need for manual tape measurements and reducing both time and human error.
Solution Approach 2:
The patent uses visual markers and target objects that can be captured via image copying. The calibration targets are placed at specific locations, and their positions are determined through image capture and processing, creating a digital copy of the physical measurement process that is more accurate and efficient.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method reduces human error and time consumption in calibrating vehicle sensors by providing an accurate and efficient way to place calibration targets using optical sensors and augmented reality, replacing traditional measuring methods.
Implementation Method 1
Capturing image data of a target object located in a workspace using the optical sensor
Implementation Method 2
The placement array of calibration locations is displayed on a display communicatively coupled to the processor in an augmented reality depiction of the workspace
Data Source
AI summary
A system and method for displaying a placement array of calibration locations, including capturing image data of a target object located in a workspace using an optical sensor communicatively coupled to a processor. Classification data is received from a database, based on the image data of on the target object within the view of the optical sensor. An origin point of the placement array of calibration locations based on the image data is determined. A plurality of calibration positions for the workspace in relation to the origin point is retrieved from the database, where the calibration locations are based on the classification data from the image data. The placement array of calibration locations is displayed on a display communicatively coupled to the processor in an augmented reality depiction of the workspace, where the placement array of calibration locations is oriented in the workspace based on the origin point.