The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Muscle Stiffness based Intent Recognition Method for Controlling Wearable Robot

착용형 로봇을 제어하기 위한 근경도 기반의 의도 인식 방법

  • Yuna Choi (Department of Electrical and Electronic Engineering, Hanyang University) ;
  • Junsik Kim (Department of Electrical and Electronic Engineering, Hanyang University) ;
  • Daehun Lee (Department of Electrical and Electronic Engineering, Hanyang University) ;
  • Youngjin Choi (Department of Electrical and Electronic Engineering, Hanyang University)
  • Received : 2023.09.20
  • Accepted : 2023.10.31
  • Published : 2023.11.30
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Abstract

This paper recognizes the motion intention of the wearer using a muscle stiffness sensor and proposes a control system for a wearable robot based on this. The proposed system recognizes the onset time of the motion using sensor data, determines the assistance mode, and provides assistive torque to the hip flexion/extension motion of the wearer through the generated reference trajectory according to the determined mode. The onset time of motion was detected using the CUSUM algorithm from the muscle stiffness sensor, and by comparing the detection results of the onset time with the EMG sensor and IMU, it verified its applicability as an input device for recognizing the intention of the wearer before motion. In addition, the stability of the proposed method was confirmed by comparing the results detected according to the walking speed of two subjects (1 male and 1 female). Based on these results, the assistance mode (gait assistance mode and muscle strengthening mode) was determined based on the detection results of onset time, and a reference trajectory was generated through cubic spline interpolation according to the determined assistance mode. And, the practicality of the proposed system was also confirmed by applying it to an actual wearable robot.

Keywords

Acknowledgement

This project was supported in part by the Technology Innovation Program funded by the Korean Ministry of Trade, industry and Energy, (20017345), and in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2019R1A2C1088375), Republic of Korea

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