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Genetic Algorithm-based Discrete Continuum Robot Design Methodology for Transoral Slave Robotic System

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Total unit number, unit length, and maximum bending angle of units are major design parameters in a discrete continuum robot. In this paper, a discrete continuum robot design methodology is suggested to determine the major design parameters for the transoral robotic surgery using a genetic algorithm (GA) based parameter optimization. If the transoral passage of a patient is reconstructed, a transoral passage-optimized discrete continuum robot can be designed using the proposed design methodology. In the proposed design methodology, a unit with a ball-socket joint is chosen to satisfy the clinical design requirements of a transoral continuum robot; moreover, the kinematics of the section in the discrete continuum robot is analyzed. Using these results, a two-section tendon-driven discrete continuum robot is designed to follow a reference transoral passage with minimal control effort by parametric optimization using a GA. The effectiveness of the proposed methodology is shown through an example using path trackability simulation and validation tests were performed to compare the design assumptions and real situations.

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Correspondence to Youngjin Moon.

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This research was jointly supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2021R1A2C3005763 and 2021R1C1C2006999), by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health Welfare, Korea (grant number: HI17C2410), and by a grant (2022IP0070) from the Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea.

Yeoun-Jae Kim received his B.S. and M.S. degrees in mechanical engineering from Kookmin University and Seoul National University, Korea, in 2000 and 2002, respectively, and a Ph.D. degree in robotics program from KAIST, in 2015. From 2015 to 2018, he was a researcher with Biomedical Research Engineering, National Cancer Center, Korea and currently a Research Fellow with Biomedical Engineering Research Center, Asan Medical Center, Korea. His research interests include medical robotics, control engineering, and applied mathematics.

Jueun Choi is in an M.S. degree course in the Department of Biomedical Engineering, College of Medicine, University of Ulsan, Korea. She received her B.S. degree in biomedical engineering from University of Ulsan, Korea. Her current research interests include medical robotic system control algorithm development and reinforcement learning, and robotic systems with medical purpose such as surgery and intervention.

Jaesoon Choi received his B.S. degree in control and instrumentation engineering and his M.S. and Ph.D. degrees in biomedical engineering from Seoul National University, Seoul, Korea, in 1995, 1997, and 2003, respectively. He had predoctoral training at the Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA, from 1999 to 2000. From 2003 to 2006, he had postdoctoral training and worked as a Staff Researcher at Research Institute, National Cancer Center, Seoul. From 2007 to 2012, he was a Research Professor at Korea Artificial Organ Center, College of Medicine, Korea University, Seoul. He is currently an Associate Professor at the Department of Biomedical Engineering, University of Ulsan College of Medicine and Asan Medical Center, Seoul. His research interests include computer-aided surgery and intervention and mechatronics system application in biomedicine.

Youngjin Moon received his Ph.D. degree in mechanical and aerospace engineering from the University of Florida, Gainesville, FL, USA, in 2011. He is with Asan Medical Center and University of Ulsan College of Medicine, Seoul, Korea as a Research Associate Professor. His research interests include design and analysis of kinematic mechanisms, and robotic systems with medical purpose such as surgery, intervention, and rehabilitation.

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Kim, YJ., Choi, J., Choi, J. et al. Genetic Algorithm-based Discrete Continuum Robot Design Methodology for Transoral Slave Robotic System. Int. J. Control Autom. Syst. 20, 3361–3371 (2022).

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  • Continuum robot
  • design optimization
  • genetic algorithm
  • master-slave robotic system
  • tendon-driven actuation
  • transoral passage
  • transoral surgery