IEMEK Journal of Embedded Systems and Applications (대한임베디드공학회논문지)

Institute of Embedded Engineering of Korea (대한임베디드공학회)
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Scene Generation of CNC Tools Utilizing Instant NGP and Rendering Performance Evaluation

Instant NGP를 활용한 CNC Tool의 장면 생성 및 렌더링 성능 평가

  • Received : 2024.01.08
  • Accepted : 2024.02.27
  • Published : 2024.04.30
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Abstract

CNC tools contribute to the production of high-precision and consistent results. However, employing damaged CNC tools or utilizing compromised numerical control can lead to significant issues, including equipment damage, overheating, and system-wide errors. Typically, the assessment of external damage to CNC tools involves capturing a single viewpoint through a camera to evaluate tool wear. This study aims to enhance existing methods by using only a single manually focused Microscope camera to enable comprehensive external analysis from multiple perspectives. Applying the NeRF (Neural Radiance Fields) algorithm to images captured with a single manual focus microscope camera, we construct a 3D rendering system. Through this system, it is possible to generate scenes of areas that cannot be captured even with a fixed camera setup, thereby assisting in the analysis of exterior features. However, the NeRF model requires considerable training time, ranging from several hours to over two days. To overcome these limitations of NeRF, various subsequent models have been developed. Therefore, this study aims to compare and apply the performance of Instant NGP, Mip-NeRF, and DS-NeRF, which have garnered attention following NeRF.

Keywords

Acknowledgement

본 논문은 2024년 산업통상자원부 산업기술국제협력 (R&D)의 지원을 받아 수행하고 있는 3차원 비전 측정 기반, 200 마이크로미터 정밀도를 보장하는 정밀 생산공정 로봇 자동 제어 솔루션 개발 및 실증 [P0026191]과 국가과학기술연구회의의 선행융합연구사업의 재구성 가능한 초고속 저전력 광학 물리신경망 연산장치 개발을 위한 선행연구 [과제 고유번호:CPS22081-100]의 지원을 받아 수행된 연구임.

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