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수정된 RLS 기반으로 관절 토크 센서를 이용한 로봇에 가해진 외부 힘 예측 및 펙인홀 작업 구현 KCI 등재

External Force Estimation by Modifying RLS using Joint Torque Sensor for Peg-in-Hole Assembly Operation

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로봇학회논문지 (The Journal of Korea Robotics Society)
한국로봇학회 (Korea Robotics Society)
초록

In this paper, a method for estimation of external force on an end-effector using joint torque sensor is proposed. The method is based on portion of measure torque caused by external force. Due to noise in the torque measurement data from the torque sensor, a recursive least-square estimation algorithm is used to ensure a smoother estimation of the external force data. However it is inevitable to create a delay for the sensor to detect the external force. In order to reduce the delay, modified recursive least-square is proposed. The performance of the proposed estimation method is evaluated in an experiment on a developed six-degree-of-freedom robot. By using NI DAQ device and Labview, the robot control, data acquisition and The experimental results output are processed in real time. By using proposed modified RLS, the delay to estimate the external force with the RLS is reduced by 54.9%. As an experimental result, the difference of the actual external force and the estimated external force is 4.11% with an included angle of 5.04° while in dynamic state. This result shows that this method allows joint torque sensors to be used instead of commonly used external sensory system such as F/T sensors.

목차
Abstract
 1. 서 론
 2. 로봇 하드웨어 및 토크 센서 구성
  2.1 로봇 하드웨어
  2.2 토크 센서
 3. 외부 힘 예측 모델
  3.1 유연관절 로봇 시스템
  3.2 외부 힘 예측 : Recursive least square
  3.3 외부 힘 예측 : Modified recursive least square
 4. 실험 및 결과
  4.1 Modified recursive least square 검증
  4.2 외부 힘 예측 실험
  4.3 펙인홀 작업
 5. 결 론
 Reference
저자
  • 정유석(Mechanical Engineering, Sogang University) | Yoo-Seok Jeong
  • 이철수(Mechanical Engineering, Sogang University, Shinsu-Dong, Mapo-Gu, Seoul, Korea) | Cheol-Soo Lee Corresponding author