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Design of a Haptic Brake Based on Magnetorheological Fluid for VR-based Laparoscopic Training

  • Jun Sik Shin (Department of Mechanical Engineering, Konkuk University) ;
  • Yoon-Gi Ku (Department of Mechanical Engineering, Konkuk University) ;
  • Jin‐Ho Choi (Department of Mechanical Engineering, Konkuk University) ;
  • JoonHyeok Kang (Department of Mechanical Engineering, Konkuk University) ;
  • Woo Joo Kim (Department of Mechanical Engineering, Konkuk University) ;
  • Young-Hwan Park (Department of Electronic Engineering, Korea National University of Transportation) ;
  • Tae-Heon Yang (Department of Mechanical Engineering, Konkuk University) ;
  • Dongbum Pyo (Human-Centric Robotics R&D Department, Korea Institute of Industrial Technology)
  • 투고 : 2024.10.06
  • 심사 : 2024.10.16
  • 발행 : 2024.11.30

초록

This study proposes the design of a compact haptic actuator that can be integrated into laparoscopic scissors. In laparoscopic surgery, surgical proficiency is crucial owing to visual and spatial constraints, and a haptic feedback device with diverse force profiles can significantly contribute to skill improvement. Active actuators like AC or DC motors are too bulky for handheld devices like haptic laparoscopic scissors and suffer from instability issues that disrupt the interaction with the physical environment. To address these constraints, we designed a haptic brake based on the properties of magnetorheological (MR) fluid. The proposed haptic brake can generate a torque of up to 78.4 N·mm using the viscosity change of MR fluid under a magnetic field, with a power consumption of 1.5 W. Simulation results and theoretical calculations were used to derive the optimum design variables, enabling the implementation of a compact and efficient haptic feedback mechanism. This study is expected to contribute to enhancing the performance of laparoscopic-surgery simulators, thereby improving the realism and user experience of virtual surgical training by providing effective haptic feedback in actual laparoscopic surgical environments.

키워드

과제정보

Shin Jun Sik and Koo Yoon-Gi contributed equally to this work. This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT) (No.2022-0-01049, Development of teaching-less product assembly system for smart factory based on autonomous robot task planning and manipulation) and National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)(RS-2024-00342395).

참고문헌

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