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ColibriDoc: An Eye-in-Hand Autonomous Trocar Docking System.
Shervin Dehghani1, Michael Sommersperger1, Junjie Yang2
1Department of Computer Science in Technische Universität München, München 85748 Germany.
Summary
This study introduces an autonomous robotic system for retinal surgery, simplifying instrument insertion. The platform uses computer vision for precise trocar docking, enhancing surgical workflow intuitiveness.
Area of Science:
- Ophthalmology
- Robotics
- Computer Vision
Background:
- Retinal surgery demands high dexterity, with robotic assistance showing promise for improved outcomes.
- Current robotic systems face challenges in autonomous trocar docking and instrument insertion, adding cognitive load.
- Developing intuitive robotic solutions is crucial for integrating advanced surgical tools into clinical practice.
Purpose of the Study:
- To present an autonomous platform for robotic trocar docking in retinal surgery.
- To simplify the initial setup phase of robotic-assisted retinal procedures.
- To enhance the intuitiveness of robotic systems for clinical integration.
Main Methods:
- A robotic system equipped with an end-effector-mounted camera was developed.
- Computer vision algorithms were employed to estimate trocar position and pose.
- The robot autonomously aligned and navigated instruments to the Trocar Entry Point (TEP) for insertion.
Main Results:
- The system accurately estimated trocar position and pose.
- Repeatable autonomous docking of the trocar was achieved.
- The proposed method demonstrated successful autonomous instrument insertion.
Conclusions:
- Autonomous trocar docking is feasible using a vision-guided robotic system.
- The developed platform reduces setup complexity and cognitive effort in robotic retinal surgery.
- This approach enhances the integration of robotic systems into the clinical workflow for retinal procedures.

