Uploaded June 2015 | Updated September 2026, 9 hours ago
This talk was given by undergraduate student Cenk Baykal during the 9th Annual Undergraduate Research Symposium in 2015. Cenk‘s research was supervised by Dr. Ron Alterovitz.
“Design Optimization Algorithms for Concentric Tube Medical Robots”
Concentric tube robots are tentacle-like surgical robots that can bend around anatomical obstacles to access hard-to-reach surgical targets. These robots have potential to enable safer, minimally invasive interventions to many sites in the human body. Concentric tube robots can be built to facilitate easy swapping out of their components to deeply customize their behavior. Customizing the design of these robots can potentially enable different surgical procedures on a variety of patients. In this presentation, I will present design optimization algorithms for concentric tube robots capable of generating a single or sets of concentric tube robot designs that can collectively maximize the reachable volume of a given goal region in the human body. I will summarize mathematical analysis proving the asymptotic optimality of our algorithm used to optimize a single design and results supporting the favorable algorithmic properties of our method. I will also show results demonstrating the effectiveness of our algorithms in a clinical scenario involving minimally invasive lung biopsy for early-stage lung cancer diagnosis.
Cenk Baykal is a senior undergraduate student majoring in Computer Science and Mathematics. In addition to his coursework, he enjoys participating in undergraduate research in Robotics and Artificial Intelligence (AI). He is particularly interested in developing algorithms based on sound mathematical foundations that have potential to enable or facilitate the use of intelligent agents to complete a wide variety of tasks in a successful way. After he graduates from UNC in May, he will be a Ph.D. student at MIT in the Computer Science and Artificial Intelligence Laboratory.
http://cs.unc.edu/academics/undergraduate/symposium/symposium-2015/
This talk was given by undergraduate student Cenk Baykal during the 9th Annual Undergraduate Research Symposium in 2015. Cenk‘s research was supervised by Dr. Ron Alterovitz.
“Design Optimization Algorithms for Concentric Tube Medical Robots”
Concentric tube robots are tentacle-like surgical robots that can bend around anatomical obstacles to access hard-to-reach surgical targets. These robots have potential to enable safer, minimally invasive interventions to many sites in the human body. Concentric tube robots can be built to facilitate easy swapping out of their components to deeply customize their behavior. Customizing the design of these robots can potentially enable different surgical procedures on a variety of patients. In this presentation, I will present design optimization algorithms for concentric tube robots capable of generating a single or sets of concentric tube robot designs that can collectively maximize the reachable volume of a given goal region in the human body. I will summarize mathematical analysis proving the asymptotic optimality of our algorithm used to optimize a single design and results supporting the favorable algorithmic properties of our method. I will also show results demonstrating the effectiveness of our algorithms in a clinical scenario involving minimally invasive lung biopsy for early-stage lung cancer diagnosis.
Cenk Baykal is a senior undergraduate student majoring in Computer Science and Mathematics. In addition to his coursework, he enjoys participating in undergraduate research in Robotics and Artificial Intelligence (AI). He is particularly interested in developing algorithms based on sound mathematical foundations that have potential to enable or facilitate the use of intelligent agents to complete a wide variety of tasks in a successful way. After he graduates from UNC in May, he will be a Ph.D. student at MIT in the Computer Science and Artificial Intelligence Laboratory.
http://cs.unc.edu/academics/undergraduate/symposium/symposium-2015/
