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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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본 연구에서는 자율 주행형 태양광 패널 청소 로봇에서 패널의 영상처리를 통해 지나가는 패턴을 세고, 모터 엔코더와 관성 센서 데이터를 융합하는 위치 인식 알고리즘을 개발하였다.
로봇 바닥의 카메라 영상처리를 통하여 태양광 패널의 라인을 검출한다. 검출한 라인을 실시간으로 추적하여 로봇의 움직임에 따른 라인의 위치 변화를 감지하고, 이를 통해 로봇의 위치를 추정하였다. 로봇의 속도에 따른 라인 검출 데이터의 보정을 통해 저가의 카메라 센서로부터 신뢰할 수 있는 위치 데이터를 확보하였다.
휠 엔코더 정보와 관성 센서에서 측정한 데이터를 확장 칼만 필터로 융합하여 패널의 라인 사이에서 로봇의 위치를 추정하였다.
알고리즘의 효과를 확인하기 위해 확장 칼만 필터만을 사용하여 얻은 위치 데이터와 영상처리만을 통해 얻은 위치 ㅔ이터 결과 값과 비교하였다.
로봇 바닥의 카메라 영상처리를 통하여 태양광 패널의 라인을 검출한다. 검출한 라인을 실시간으로 추적하여 로봇의 움직임에 따른 라인의 위치 변화를 감지하고, 이를 통해 로봇의 위치를 추정하였다. 로봇의 속도에 따른 라인 검출 데이터의 보정을 통해 저가의 카메라 센서로부터 신뢰할 수 있는 위치 데이터를 확보하였다.
휠 엔코더 정보와 관성 센서에서 측정한 데이터를 확장 칼만 필터로 융합하여 패널의 라인 사이에서 로봇의 위치를 추정하였다.
알고리즘의 효과를 확인하기 위해 확장 칼만 필터만을 사용하여 얻은 위치 데이터와 영상처리만을 통해 얻은 위치 ㅔ이터 결과 값과 비교하였다.
목차
요약 ······················································································································ ⅰ표목차 ······························································································································ ⅲ그림목차 ·························································································································· ⅳ기호설명 ·························································································································· ⅵI. 서 론 ······························································································································ 11. 연구 배경 및 목적······································································································· 1II. 영상 처리 ····················································································································· 21. 라인 검출······················································································································ 32. 라인 카운트·················································································································· 73. 임계 값 보정 ··············································································································· 9III. 관성 측정 센서 ········································································································ 111. 로봇 Heading 각 계산 ····························································································· 122. 검출 라인의 수평-수직 판별··················································································· 13IV. 위치 인식 알고리즘 ······························································································· 141. 기구학 모델링 ( Kinematic modeling ) ································································· 142. 확장 칼만필터 기반 위치인식 알고리즘 ······························································· 15V. 실험 결과 ·················································································································· 201. 실험 환경···················································································································· 202. 실험 결과···················································································································· 22Ⅵ. 결론 ··························································································································· 25참고문헌 ·························································································································· 26영문초록(Abstract) ········································································································· 28
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