카메라 기반 객체의 위치인식을 위한 왜곡제거 및 오검출 필터링 기법Distortion Removal and False Positive Filtering for Camera-based Object Position Estimation
- Other Titles
- Distortion Removal and False Positive Filtering for Camera-based Object Position Estimation
- Authors
- 진실; 송지민; 최지호; 진용식; 정재진; 이상준
- Issue Date
- Feb-2024
- Publisher
- 대한임베디드공학회
- Keywords
- Deep learning; Computer vision; Manipulator robot; Distance estimation; Object detection
- Citation
- 대한임베디드공학회논문지, v.19, no.1, pp 1 - 7
- Pages
- 7
- Journal Title
- 대한임베디드공학회논문지
- Volume
- 19
- Number
- 1
- Start Page
- 1
- End Page
- 7
- URI
- https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/28530
- DOI
- 10.14372/IEMEK.2024.19.1.1
- ISSN
- 1975-5066
- Abstract
- Robotic arms have been widely utilized in various labor-intensive industries such as manufacturing,
agriculture, and food services, contributing to increasing productivity. In the development of industrial robotic arms,
camera sensors have many advantages due to their cost-effectiveness and small sizes. However, estimating object
positions is a challenging problem, and it critically affects to the robustness of object manipulation functions. This
paper proposes a method for estimating the 3D positions of objects, and it is applied to a pick-and-place task. A deep
learning model is utilized to detect 2D bounding boxes in the image plane, and the pinhole camera model is employed
to compute the object positions. To improve the robustness of measuring the 3D positions of objects, we analyze the
effect of lens distortion and introduce a false positive filtering process. Experiments were conducted on a real-world
scenario for moving medicine bottles by using a camera-based manipulator. Experimental results demonstrated that the
distortion removal and false positive filtering are effective to improve the position estimation precision and the
manipulation success rate.
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