Research into Deep Learning for the Control of Concentric Tube Robots and other Continuum Based Robots

Lead Research Organisation: King's College London
Department Name: Imaging & Biomedical Engineering

Abstract

Concentric Tube Robots (CTRs) are a form of continuum robotics. They are created by nesting a number of pre-curved Nitinol tubes. They could be highly beneficial for a number of interventions due to the small size of the system. Also because of the system's high dexterity at the end effector and ability to create a snake like shape. Producing a higher effectiveness in particular interventions, such as in the field of ophthalmology, relative to the current state of the art.

The robotic system is controlled by translating or rotating the tubes in a given manner. However due to the complexity of the kinematics due to internal friction tension and other forces. Also the addition of external forces increases the complexity of the control needed. I am proposing research into the use of a number of different Machine Learning methodologies to replace the current models used.

The first steps of this is the creation and validation of a system which is able to record accurate datasets. I will use 2 methods to collect data, stereoscopic visual light camera and EM trackers. I will also work on the implementation of a method to apply forces at multiple locations along the length of the CTR.

Along side this, I will be completing research into the current state of the art in this field. This includes the validation of A. Kuntz, R. Grassmann and K. Iyengar's models. Each looking at the CTR Kinematics in a different method ranging from reinforcement learning to fully connected layers. I will then build on this to make a network which will also work with hyper parameters and external forces as an input. Creating a more complete model for interventional use.
Taking my knowledge learned from these 2 layers I plan to translate my models to control a CTR in realtime with the use of a haptic device. This is the base requirement of tele-operated system. This will be used for such systems as VIPER, which is a CTR created by RVIM lab. Its end usage will be for interocular surgery.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/R513064/1 01/10/2018 30/09/2023
2338607 Studentship EP/R513064/1 06/07/2020 13/11/2025 Ross Henry
EP/T517963/1 01/10/2020 30/09/2025
2338607 Studentship EP/T517963/1 06/07/2020 13/11/2025 Ross Henry