Vision Module for Automatic Tracking on Bedside Intelligent Scope-Holding Surgical Robot System.

Area of Science:

• Robotics
• Surgical Technology
• Computer Vision

Background:

• Bedside intelligent surgical robots require advanced instrument tracking.
• Manual endoscope holding limits efficiency and precision in endoscopic procedures.

Purpose of the Study:

• To develop active following technology for a surgical robot's mirror-holding arm.
• To enable real-time automatic tracking of surgical instruments during procedures.

Main Methods:

• Enhanced a semantic segmentation network with new surgical clamp datasets.
• Determined clamp position and robot arm motion parameters.
• Designed and verified a control rate using an endoscopic surgery simulation platform.

Main Results:

• The collaborative robot arm achieved an average time of 2.51 seconds to reach the field of view center.
• The variance in reaching time was 0.32 seconds.

Conclusions:

• The developed robotic arm technology effectively replaces manual endoscope holding.
• This automation has significant potential to improve the efficiency of endoscopic surgical procedures.