CTR Design Optimization
Concentric tube robots have potential for use in a wide variety of surgical procedures due to their small size, dexterity, and ability to move in highly curved paths. Unlike most existing clinical robots, the design of these robots can be developed and manufactured on a patient- and procedure- specific basis. The design of concentric tube robots typically requires significant computation and optimization, and it remains unclear how the surgeon should be involved. We have proposed multiple approaches to solving this design optimization problem.
In one approach, we propose a computational framework that can efficiently optimize a robot design and a motion plan to enable safe navigation through the patient’s anatomy. The current framework is the first fully gradient-based method for CTR design optimization and motion planning, enabling an efficient and scalable solution for simultaneously optimizing continuous variables, even across multiple anatomies. The framework is demonstrated using two clinical examples, laryngoscopy and heart biopsy, where the optimization problems are solved for a single patient and across multiple patients, respectively.
Recent relevant papers:
J. Lin, C. Girerd, J. Yan, J. Hwang, and T.K. Morimoto. "A Generalized Framework for Concentric Tube Robot Design Using Gradient-Based Optimization." IEEE Transactions on Robotics. 2022.
Open-source framework:
In a second approach, we propose to use a virtual reality-based design environment for surgeons to easily and intuitively visualize and design a set of concentric tube robots for a specific patient and procedure. We also show a resulting concentric tube robot design, created by a pediatric urologist to access a kidney stone in a pediatric patient.
