Imaging Sensor Calibration Target for Mobile Automation
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Solution Overview
Problem
Tracking the status of objects in complex environments, such as retail facilities, is time-consuming and error-prone when performed by human staff, and existing calibration procedures for mobile apparatuses with cameras are cumbersome.
Innovation Solution
A method and apparatus for sensor calibration using an imaging controller that captures images of a calibration target with predefined indicia, decodes heights, generates transforms between image and common reference frames, and determines camera position for accurate mapping of subsequent images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration procedures are used for mobile apparatuses with cameras, then the camera can be calibrated to map images to the environment, but the calibration process becomes time-consuming and cumbersome
Solution Approach 1:
The system performs preliminary mapping of the environment using map data before calibration is needed. When calibration occurs, the system compares current image features with pre-mapped environment data to rapidly determine camera position and orientation, avoiding time-consuming traditional calibration procedures.
Solution Approach 2:
The system introduces map data as an intermediary element between the camera and the environment. By comparing image features with pre-stored map data, the system can rapidly calculate camera calibration parameters without requiring lengthy traditional calibration processes.
2Reliability
If manual tracking of object status is performed by human staff in complex environments, then objects can be monitored, but the process becomes time-consuming and error-prone
Solution Approach 1:
The system enables automated self-service tracking where the mobile apparatus autonomously captures images, compares them with map data, and updates object status without human intervention. This eliminates manual tracking errors and significantly reduces the time required for monitoring objects in complex environments.
Solution Approach 2:
The system replaces manual mechanical tracking with automated imaging and computational analysis. The camera captures visual data, and the processing system automatically compares image features with map data to track object status, eliminating human labor and associated errors.
3Measurement precision
If comprehensive calibration data is collected for accurate mapping, then mapping precision improves, but the complexity of the calibration procedure increases
Solution Approach 1:
The system extracts only the essential calibration information needed for accurate mapping by comparing image features with pre-stored map data. Instead of collecting comprehensive calibration data through complex procedures, the system extracts position and orientation parameters directly from feature matching between images and map data.
Data Source
AI summary
A sensor calibration target configured for sensor calibration relative to a common frame of reference is disclosed. The sensor calibration target comprises a first surface at a first predefined depth bearing a first set of indicia at respective first heights and having respective first predefined shifts, each of the first indicia encoding a corresponding first height. The sensor calibration target further comprises a second surface at a second predefined depth bearing a second set of indicia at respective second heights and having respective second predefined shifts, each of the second indicia encoding a corresponding second height.