메뉴 건너뛰기

ENG

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
(한국기술교육대학교) (한국기술교육대학교) (한국기술교육대학교)
저널정보
제어로봇시스템학회 제어로봇시스템학회 논문지 제어로봇시스템학회 논문지 제27권 제8호
발행연도
수록면
578 - 585 (8page)
DOI
10.5302/J.ICROS.2021.21.0052

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
이 논문의 연구방법이 궁금하신가요?
🏆
연구결과
이 논문의 연구결과가 궁금하신가요?
AI에게 요청하기
추천
검색
질문

초록· 키워드

This paper proposes an AI-based welding robot 3D vision module and manipulator control system for welding automation. With conventional welding robots, welding is performed only at the designated welding points through robot teaching; however, the difficulty with this method is that the position of the welding point changes due to the tolerance (gap) of the welding object. To solve this problem, we automatically recognized the welding points using a deep learning-based object detection model called YOLOv4. The time required for labeling was thus reduced through a deep learning labeling tool that uses an existing learned weights file. To control the robot with the recognized welding point, a hand/eye calibration method calculating the homogeneous transformation matrix between the robot and the camera was adopted. Additionally, to correct the final robot control error caused due to calibration and camera depth errors, the control precision at the welding point was improved through interpolation method. The system has been verified by conducting sufficient number of experiments in a non-destructive formwork welding environment.
#Deep learning #Welding robot #Vision module #Robot vision system
상세정보 수정요청해당 페이지 내 제목·저자·목차·페이지
정보가 잘못된 경우 알려주세요!

목차

  1. Abstract
  2. I. 서론
  3. II. AI 기반의 용접로봇 3D 비전모듈 및 용접 시스템
  4. III. 실험 환경 및 실험 결과
  5. IV. 결론 및 추후 과제
  6. REFERENCES

참고문헌

참고문헌 신청

최근 본 자료

전체보기
260319_딥리서치
260319_AI리더
260304_새학기에이전트
260122_AIagent
260304_아그논문롤
260127_아그논문
260127_AI뷰어
UCI(KEPA) : I410-ECN-0101-2021-003-001917598