Design Optimization Algorithms for Concentric Tube Robots (2015)

Undergraduates: Cenk Baykal, Luis Torres

Faculty Advisor: Ron Alterovitz
Department: Computer Science

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Concentric tube robots are tentacle-like, medical robots that have potential to enable novel, minimally-invasive surgical procedures. These robots are composed of pre-curved,
nested tubes which can be rotated and translated to cause the robot¿¿¿s shape to change and enable maneuverability. Due to the complex interactions between the robot¿¿¿s tubes, the physical specifications of each of the robot¿¿¿s tubes, such as curvature and length, significantly affect the set of clinical targets that the robot can reach. Hence, a concentric tube robot with design parameters that are appropriately chosen for a particular patient and clinical application will be more capable in reaching surgery-specific clinical targets than will concentric tube robots with generic designs. In this presentation, I present my work on design optimization algorithms for concentric tube robots, i.e. computational methods that can optimize the design parameters of concentric tube robot on a patient- and application-specific basis. I also provide results showing the effectiveness of our approach in a medically motivated, simulated scenario involving the use of concentric tube robots in minimally invasive lung biopsy for early-stage lung cancer diagnosis.