Surgical Tool Frame Transform Estimation for Image-Aligned Robotic Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Precise control of surgical instruments in medical robotic systems is challenging when the position and orientation of one frame is unknown, jeopardizing patient safety and procedure success.
Innovation Solution
A system and method for estimating an unknown frame transform using image capturing systems to determine the position and orientation of a tool frame relative to an image frame, enabling accurate movement control of surgical instruments based on input from a user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional open surgery techniques are used, then surgical control is straightforward, but patient trauma, pain, and recovery time increase
Solution Approach 1:
The patent replaces direct mechanical surgical control with a robotic system that uses image capturing and computational geometry to determine tool position and orientation. The robotic manipulator system substitutes manual mechanical operations with automated control based on visual feedback, enabling minimally invasive procedures that reduce tissue injury while maintaining surgical precision.
2Manufacturing precision
If frame transform is unknown in robotic control, then system complexity is reduced, but control precision deteriorates
Solution Approach 1:
The patent introduces an intermediary approach by using image capturing systems and fiducial markers as mediators to bridge the unknown frame transform. Instead of directly computing the complex transform between tool frame and image frame, the system uses intermediate reference points (fiducials) that are detectable in images to establish the relationship, thereby achieving precise control without requiring complete knowledge of all frame transforms.
Solution Approach 2:
The system implements feedback by continuously capturing images of the surgical site and tool, detecting fiducial marker positions in these images, and using this visual feedback to compute and update the frame transform. This closed-loop feedback mechanism enables real-time adjustment and maintains control precision despite the inherent complexity of the transform computation.
3Measurement precision
If image capturing system is added to determine frame transform, then control precision is improved, but device complexity increases
Solution Approach 1:
The patent applies universality by designing the image capturing system to serve multiple functions: capturing the surgical site for visualization, detecting fiducial markers for frame transform computation, and providing feedback for control. This multi-functional approach improves measurement precision while limiting the increase in device complexity by making a single system component perform several essential roles.
Data Source
AI summary
A system includes a control means for receiving an input from a user, a manipulator means configured to support a tool having a tool frame, and processing means configured to perform a method. The method involves receiving, from an image capturing system with an image frame, one or more images. The tool is visible in the one or more images. The method further involves determining an estimated frame transform based on the one or more images. The estimated frame transform is used in defining an unknown frame transform between the image frame and the tool frame. The method also involves determining, in response to the input received at the control means, an output movement for the tool based on the estimated frame transform, and causing movement of the tool based on the output movement.