학술논문

Development of a flexible endoscopic robot with autonomous tracking control ability using machine vision and deep learning
Document Type
article
Source
Mechanical Sciences, Vol 15, Pp 223-236 (2024)
Subject
Materials of engineering and construction. Mechanics of materials
TA401-492
Language
English
ISSN
2191-9151
2191-916X
Abstract
A flexible endoscopic robot is designed to solve the problem that it is difficult for auxiliary doctors to maintain a stable visual field in traditional endoscopic surgery. Based on geometric derivation, a motion control method under the constraint of the remote center motion (RCM) of the robot system is established, and a set of circular trajectories are planned for it. The RCM error of the robot during operation and the actual trajectory of the robot end in three-dimensional space are obtained through the motion capture system. The end of the robot is controlled by the heterogeneous primary–secondary teleoperation control algorithm based on position increments. Finally, the RTMDet deep learning object detection algorithm was selected to identify and locate surgical instruments through comparative experiments, and the autonomous tracking control was completed based on visual guidance. In the process of autonomous tracking, the RCM error was less than 1 mm, which met the actual surgical requirements.