Access Type

Open Access Thesis

Date of Award

January 2016

Degree Type

Thesis

Degree Name

M.S.

Department

Electrical and Computer Engineering

First Advisor

Abhilash Pandya

Abstract

Camera control methods play a significant role in remote surgery. Two methods have been developed to control the camera arm of the da Vinci Surgical System: a standard clutch-based method for manual movement of the camera and an autonomous camera (auto-camera) method. In the standard method, the surgeon positions the camera manually using a pair of hand controllers. This happens frequently during the surgery and may serve as a distraction during surgical procedures. The second method was developed in order to help surgeon to remove the issue mentioned in the standard method. Auto-camera method enables the system to move the camera autonomously. In this method, the camera is moved with-respect-to the center of surgical tool arms with automatic zoom control ability. There are still many issues with automatically moving a camera. We will show the feasibility of an intermediate solution using an Oculus rift head mounted stereo display.

Achieving the optimal camera viewpoint with simple control methods is of utmost importance for remote surgical systems. We propose a new method to move the camera arm based on sensors within the Oculus Rift. Can a surgeon put the Oculus Rift (virtual reality headset), get a stereoscopic view and control the camera with simple head gestures? In this case, the surgeon will be able to see the 3D camera view of scope inside of the Oculus Rift and move the viewpoint by his/her head orientation. Position and orientation of the Oculus rift is measured by an inertial measuring unit and optical tracking sensors within the Oculus platform. These data can be used to control the position and orientation of the camera arm.

In this thesis, a complete system will be created based on the Robot Operating System (ROS) and a 3D simulation of the da Vinci robot in RViz. In addition, a usability study will be conducted to analyze system accuracy. For this system evaluation, headset orientation will be compared to corresponding orientation of the camera in simulation. We will also check whether subjects can use the system comfortable during a simple operation.

In this study, we propose controlling of the camera arm by Oculus Rift as a new method for camera control. It is anticipated that the headset movement will be the same as its corresponding simulation in RViz (simulation environment for the robot). We anticipate that our results will demonstrates feasibility for this method to control a camera. We will propose next steps for testing this system on the da Vinci hardware leading towards a system for the operating room of the future.

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