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  Development of an Optical Shape Sensing Method Using Optoelectronic Sensors for Soft Flexible Robotic Manipulators in Minimally Invasive Surgery

   Aerospace Engineering

   Applications accepted all year round  Self-Funded PhD Students Only

About the Project

About the programme

Over the last two decades, many soft continuum manipulators have been developed by many academic institutions and industries for MIS (minimally invasive surgery), endoscopy, and colonoscopy because they can easily access the small or narrow opening in the body during a medical operation. Their body is comprised of soft material, giving them flexibility to allow them to access a large workspace so they can easily not only pass through the small or narrow opening, but also minimise the excessive force on the soft tissue or the organs in the body. In developing the soft continuum manipulators, many scientists have faced a number of daunting obstacles because of difficulties implementing cross-loop position control into the manipulator using the existing shape detection approaches. The vision approach is very simple, however, during a medical operation, organs or objects might block the manipulator, resulting the camera unable to detect its shape. There exists soft continuum manipulators successfully integrating the shape sensing modality based on Fibre Bragg grating (FBG); their sensing performances are accurate. Despite the outstanding shape sensing accuracy, its calibration method is very complicated. The device called “interrogator” which can detect strain values from the FBGs attached on the soft material body costs around £20,000, and manufacturing the shape sensor is too complex, taking a long time to fabricate.

For this reason, in this project, the student proposes to develop a new flexible continuum manipulator integrating a novel shape sensor. The new flexible continuum manipulator consists of an internal rigid structure and an external soft structure as an outer cover. The new shape sensor consists of optoelectronic sensors and flexible mechanical structures, and the optoelectronic sensors are integrated into the serially connected flexible mechanical flexures. In general, optoelectronic sensors are used to detect whether an object exists or not, or can measure distances. For the shape sensing, the optoelectronic sensors are deployed in each of the serially connected flexible mechanical structures, and they measure the distances (or deformations) in each of the flexible mechanical structure. From the measured deformation values, two (pitch and roll) or three orientations (pitch, roll, and yaw) can be estimated. Therefore, all of the estimated orientations in each of the serially connected mechanical flexures can be simplified by the rigid-link model, so the overall manipulator’s shapes can be visualised. The main advantages of this shape sensing approach include the ability to measure very accurate angles (shapes) and low cost. Optoelectronic sensors have a low electrical noise and high frequency sampling rate, allowing for speed and stability too.

In this project, the student should solve three tasks to design a new flexible continuum manipulator as follows:

1) devise a flexible mechanical flexure to measure two or three orientations using optoelectronic sensors and find a calibration method to obtain the optoelectronic sensor’s data to physical orientation values.

2) choose a driving mechanism (tendon, hydraulic, or pneumatic).

3) devise a new design on how to combine the serially connected flexible mechanical flexure with an outer cover consisting of soft material.

The supervisor is an expert on Mechanical design, Robot Dynamics, Finite Element Analysis (FEA), Mathematical Modelling, Computer-Aided Design software Packages (CREO, Solidworks, Fusion, Onshape), Computer program languages C++, C#, Python, MATLAB, Robot Operating System (ROS), Electronics, Mechatronics, and Hard/Software integration, so he will fully support your research, and the student will have a great deal of experience in publishing a lot of conference and journal papers.

Computer Science (8) Creative Arts & Design (9) Engineering (12)

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