Robot-Based Camera Registration with Mobile Calibration Markers
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Solution Overview
Problem
Camera registration in smart spaces is labor-intensive and costly, requiring experienced engineers to manually calibrate multiple environmental cameras, which is time-consuming and prone to errors.
Innovation Solution
A robot equipped with a calibration marker moves within the view of environmental cameras, allowing automatic camera registration by calculating poses using hand-eye calibration algorithms and trajectory alignment methods, reducing manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual camera registration is performed by experienced engineers, then registration accuracy and reliability are improved, but labor cost and time consumption increase significantly
Solution Approach 1:
The system enables automatic self-registration of cameras by having the robot autonomously navigate to calibration positions and capture images. The calibration algorithm automatically processes these images to determine camera poses without requiring manual intervention from experienced engineers, thus reducing both time and maintaining reliability through automated precision
Solution Approach 2:
The patent replaces the manual mechanical process of camera registration with an automated robotic system. The robot physically performs the calibration task by moving to predetermined positions and capturing images, substituting human engineer expertise with an automated mechanical system that achieves similar accuracy without time consumption
2Measurement precision
If manual camera registration is performed by experienced engineers, then registration accuracy is improved, but human error and cost increase
Solution Approach 1:
The automated system eliminates human error by performing registration tasks autonomously. The robot independently navigates to calibration positions, captures images, and the algorithm automatically processes data to determine camera poses, removing the variable of human mistake while maintaining measurement precision through consistent automated execution
Solution Approach 2:
The patent substitutes the human operator with an automated robotic system that performs measurement and calibration tasks. This replacement eliminates human error entirely while maintaining or improving measurement precision through the consistency and accuracy of the automated navigation and image capture system
3Adaptability or versatility
If multiple environmental cameras are deployed, then system functionality and coverage are improved, but registration complexity and cost increase
Solution Approach 1:
The patent creates a universal registration system where a single robot can autonomously register multiple different environmental cameras across various locations. The robot serves multiple functions: navigating to different positions, capturing calibration images for different cameras, and processing data for all cameras, thereby reducing overall system complexity despite having multiple cameras
Solution Approach 2:
The automated robot performs all registration tasks for multiple cameras independently without requiring separate manual registration processes for each camera. This self-service approach scales efficiently with the number of cameras, maintaining low complexity as the system can automatically handle any number of cameras deployed in the environment
Data Source
AI summary
The disclosure provides techniques for registering a camera into a map via a robot. A method for registering a camera into a map may include: collecting an observation of a calibration marker from an image captured by the camera, the calibration maker being attached to a robot capable of moving in a view of the camera; calculating, for the observation of the calibration marker, a transform T (camera, marker) between a camera frame of the camera and a marker frame of the calibration marker; obtaining, for the observation of the calibration marker, a transform T (world, robot) between a world frame of the map and a robot frame of the robot; and performing, when more than a predetermined number of observations of the calibration marker are collected during movement of the robot, a calibration process to calculate a transform T (world, camera) between the world frame and the camera frame based on the transform T (camera, marker) and the transform T (world, robot) for each observation of the calibration marker.