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. 2022 Jan 31:8:773830.
doi: 10.3389/frobt.2021.773830. eCollection 2021.

Development of a Robotic Surgery Training System

Robin Julia Trute  1   2   3 , Carlos Suárez Zapico  1   2   3 , Andreas Christou  1   2   3 , Daniel Layeghi  1   2   3 , Stewart Craig  1 , Mustafa Suphi Erden  1   3
Affiliations

Development of a Robotic Surgery Training System

Robin Julia Trute et al. Front Robot AI. .

Abstract

Robotic Surgery is getting widely spread and applied to more and more clinical cases due to its advantages compared to open surgery, for both the patients and surgeons. However, Robotic Surgery requires a different set of skills and learning compared to open and also laparoscopic surgery. Tele-operation for a robotic system with hand controllers, the delay in the hand commands to be translated into robotic movements, slowness of the robotic movements, remote 2D or 3D vision of the actual operation, and lack of haptic feedback are some of the challenges that Robotic Surgery poses. Surgeons need to go through an intensive training for Robotic Surgery, and the learning and skill development continues throughout their early professional years. Despite the importance of training for Robotic Surgery, there are not yet dedicated, low-cost, and widespread training platforms; rather, surgeons mostly train with the same Robotic Surgery system they use in surgery; hence institutions need to invest on a separate surgical setup for training purposes. This is expensive for the institutions, it provides very limited access to the surgeons for training, and very limited, if any, access to researchers for experimentation. To address these, we have developed in our laboratory a low-cost, and experimental Robotic Surgery Trainer. This setup replicates the challenges that a Robotic Surgery system poses and further provides widespread access through internet connected control of the actual physical system. The overall system is composed of equipment that a standard engineering laboratory can afford. In this paper, we introduce the Robotic Surgery Training System and explain its development, parts, and functionality.

Keywords: 3D vision; haptic feedback; laparoscopic skill development; minimally-invasive surgery; robotic training; stereo vision.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
(A) The setup of the robotic training system with all components in on-site control mode with 2D vision on-screen modality. (B) VR headset setup for 3D vision modality.
FIGURE 2
FIGURE 2
Overall system architecture diagram.
FIGURE 3
FIGURE 3
Actuated DOF per laparoscopic instrument.
FIGURE 4
FIGURE 4
Two Dynamixel servos mounted on the forcep to control third rotational axis and grasping motion.
FIGURE 5
FIGURE 5
Coordinates used for the calculations of the linear and angular velocities of the robot.
FIGURE 6
FIGURE 6
Visual feedback of forces that can be provided during the teleoperation of the robot by keyboard.
FIGURE 7
FIGURE 7
Instrument tip force computed based on the force-torque sensor signal.
FIGURE 8
FIGURE 8
Tool-tip position over time.
FIGURE 9
FIGURE 9
Force feedback sensation at the haptic device.
FIGURE 10
FIGURE 10
Coordinate frame conversion from force torque sensor attached to the wrist of the robot arm to the tool-tip coordinate frame.
FIGURE 11
FIGURE 11
Stereo vision setup with two wide-angle cameras in a 3D printed mount, put in right position and orientation by 3D printed hinges.
FIGURE 12
FIGURE 12
Client-Server architecture with cloud servers for remote control of the robotic training setup.
FIGURE 13
FIGURE 13
Command sending latency (left) and Video Streaming latency (right).
See this image and copyright information in PMC

References

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