Micro-object pose estimation with sim-to-real transfer learning using small dataset

Micro-object pose estimation with sim-to-real transfer learning using small dataset

Three-dimensional (3D) pose estimation of micro/nano-objects is essential for the implementation of automatic manipulation in micro/nano-robotic systems. However, out-of-plane pose estimation of a micro/nano-object is challenging, since the images are typically obtained in 2D using a scanning electr...

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Bibliographic Details
Main Authors: Bai, W. (Author), Barbot, A. (Author), Lo, B. (Author), Lo, F.P.-W (Author), Seichepine, F. (Author), Yang, G.-Z (Author), Zhang, D. (Author)
Format: Article
Language:English
Published: Nature Research 2022
Subjects:
Closed loop control systems
Deep learning
Generative adversarial networks
Labeled data
Large dataset
Micro/nano
Micro-objects
Nano-objects
Object pose
Optical microscopes
Pose-estimation
Scanning electron microscopy
Small data set
Training dataset
Transfer learning
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