RISS 학술연구정보서비스

검색
다국어 입력

http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.

변환된 중국어를 복사하여 사용하시면 됩니다.

예시)
  • 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
  • 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
닫기
    인기검색어 순위 펼치기

    RISS 인기검색어

      검색결과 좁혀 보기

      선택해제

      오늘 본 자료

      • 오늘 본 자료가 없습니다.
      더보기
      • 무료
      • 기관 내 무료
      • 유료
      • KCI등재

        Prediction and Compensation of Relative Position Error along Industrial Robot End-Effector Paths

        Antonios Angelidis,George-Christopher Vosniakos 한국정밀공학회 2014 International Journal of Precision Engineering and Vol. No.

        In on-line and especially in off-line programming of industrial robots the attainable accuracy has to be taken into account. Especially in the case of off-line programming along particular trajectories followed, neglecting position errors leads to a need for kinematic calibration procedures which, however, apply to the robot controller level. If end effector error is taken into consideration in off-line programming a compensated commanded trajectory can be programmed. This is different to well-established calibration procedures, because it keeps the original kinematic model of the robot and tries to improve accuracy along the particular trajectory of interest. In this paper, the methodology for measuring, predicting and compensating end effector position errors is presented. A straight line trajectory is used as an example in connection to a particular industrial robotic arm. Measurements are taken using white-light metrology. Based on these measurements an error prediction model is constructed by training an Artificial Neural Network. A second neural network model is trained to yield joint coordinates that minimise position error, which is proved by employing the prediction model on the results of the compensation model.

      연관 검색어 추천

      이 검색어로 많이 본 자료

      활용도 높은 자료

      해외이동버튼