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аналитика - Hand-eye calibration
사전 훈련된 이미지 모델을 사용한 완전 자동 핸드-아이 캘리브레이션: EasyHeC++
EasyHeC++는 사전 훈련된 이미지 모델과 차별화 가능한 렌더링을 활용하여 로봇 팔 유형에 관계없이 마커, 학습, 수동 작업 없이 완전 자동 핸드-아이 캘리브레이션을 달성하는 새로운 프레임워크입니다.
EasyHeC++: A Fully Automatic and Training-Free Hand-Eye Calibration System Using Pretrained Image Models
EasyHeC++ enables accurate hand-eye calibration for any robot arm without manual calibration, specialized markers, or training arm-specific neural networks by leveraging pretrained image models and differentiable rendering.
Geometry-Based Hand-Eye Calibration for Improved Accuracy and Repeatability in Robot-Assisted Procedures
The core message of this article is that the proposed Geometry-Based End-Effector Calibration (GBEC) method can enhance the repeatability and accuracy of the derived transformation between a robot's end-effector and a sensor attached to it, compared to traditional hand-eye calibration techniques.
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