Medical Robot Camera Calibration Using Dual-Camera Hand-Eye Alignment
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Solution Overview
Problem
Current methods for hand-eye calibration and geometric calibration in medical robotics are manual, error-prone, and lack precision, especially in surgical interventions where millimeter accuracy is required, necessitating a more efficient and automated solution.
Innovation Solution
An automated calibration method using two cameras, one mounted on a robot arm (eye-in-hand) and another externally (eye-on-base), which moves to detect a calibration pattern and determine transformations between the cameras and the robot, enabling simultaneous hand-eye and geometric calibration without manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration methods are used, then the calibration process can be performed with simple equipment, but the calibration precision and reliability are insufficient for surgical applications
Solution Approach 1:
A calibration object with known geometry (calibration pattern) is introduced as an intermediary between the camera and robot. This calibration object serves as a mediator that enables automated extraction of calibration data through image processing, achieving high precision without requiring complex manual measurement procedures. The calibration object includes features that can be automatically detected and measured by the camera system.
Solution Approach 2:
The system performs self-calibration through automated image capture and processing. The camera automatically captures images of the calibration object at multiple positions, and the system autonomously processes these images to extract geometric information and compute calibration parameters without requiring manual intervention or specialized calibration equipment beyond the calibration object.
2Productivity
If automated calibration is implemented, then calibration speed and accuracy improve, but the device complexity and number of required components increase
Solution Approach 1:
The calibration object serves multiple functions: it provides geometric reference features for calibration, acts as a positioning target, and enables verification of calibration accuracy. The same calibration object is used for both hand-eye calibration and geometric calibration of the camera, eliminating the need for separate calibration procedures and reducing overall system complexity despite the automated process.
Solution Approach 2:
Manual mechanical measurement and adjustment procedures are replaced with an automated optical measurement system. The camera captures images of the calibration object, and image processing algorithms automatically extract positional and orientational information, substituting manual mechanical operations with automated visual measurement to achieve faster and more accurate calibration.
3Reliability
If manual calibration procedures are used, then fewer additional devices are needed, but the calibration process becomes error-prone and time-consuming
Solution Approach 1:
The system implements automated feedback through image capture and processing. The camera captures images of the calibration object at multiple predetermined positions, and the system processes these images to compute calibration parameters. This closed-loop automated process eliminates manual measurement errors and ensures consistent, reliable calibration results while reducing the time required compared to manual procedures.
Solution Approach 2:
The calibration procedure is designed to automatically perform all necessary measurements and computations in a predetermined sequence. The system automatically moves the camera to multiple predetermined positions, captures images at each position, and processes all images to compute final calibration parameters without requiring manual intervention during the calibration process, thereby ensuring reliability and reducing time loss.
Data Source
AI summary
A method is used for calibrating a robot camera and external camera system relative to a medical robot. The robot camera is guided on an arm. The camera system has an external camera. The method includes: moving the robot camera via the robot arm during sensing and capturing; detecting a pose of a calibration pattern and/or an external tracker, each having a transformation to a pose of the external camera, and/or detecting a pose of the external camera; determining a transformation between the robot camera and external camera, and determining a field of view; moving a flange into at least three poses in the field of view and sensing the at least three poses via the external camera, and simultaneously sensing a transformation between the robot base and the flange; and performing a hand-eye calibration. The method can be used with a surgical assistance system and computer-readable storage medium.