산업용 로봇 작업장 안전시스템 개발에 대한 연구
(주)코리아스칼라
- 최초 등록일
- 2023.10.23
- 최종 저작일
- 2023.09
- 6페이지/ 어도비 PDF
- 가격 4,000원
* 본 문서는 배포용으로 복사 및 편집이 불가합니다.
서지정보
ㆍ발행기관 : 대한안전경영과학회
ㆍ수록지정보 : 대한안전경영과학회지 / 25권 / 3호
ㆍ저자명 : 김진배, 권순현, 이만수
목차
1. 서 론
1.1 연구배경
1.2 연구 목적 및 방법
2. 안전시스템 개요
2.1 YOLO 알고리즘 개요
2.2 안전시스템 개요
3. 실험 및 검증
4. 결론
영어 초록
As the importance of artificial intelligence grows rapidly and emerges as a leader in technology, it is becoming an important variable in the next-generation industrial system along with the robot industry. In this study, a safety system was developed using deep learning technology to provide worker safety in a robot workplace environment. The implemented safety system has multiple cameras installed with various viewing directions to avoid blind spots caused by interference. Workers in various scenario situations were detected, and appropriate robot response scenarios were implemented according to the worker's risk level through IO communication. For human detection, the YOLO algorithm, which is widely used in object detection, was used, and a separate robot class was added and learned to compensate for the problem of misrecognizing the robot as a human. The performance of the implemented system was evaluated by operator detection performance by applying various operator scenarios, and it was confirmed that the safety system operated stably.
참고 자료
없음
"대한안전경영과학회지"의 다른 논문
더보기 (4/9)