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Feature-aware autonomous camera pose estimation for rebar tying robots
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DOI：10.1016/j.autcon.2026.107000.png)
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Abstract
En 中文
• A feature-aware framework is proposed for autonomous camera pose estimation, tailored for robotic rebar tying. • Structure-aware algorithms for feature extraction and matching overcome the visual ambiguity of repetitive rebar cages. • A closed-loop feedback mechanism with image quality evaluation is introduced to refine and optimize the camera pose. • The proposed framework outperforms deep learning-based, structure-driven, and manual methods in reliability and efficiency. • The method's effectiveness and robustness are validated through experiments in both laboratory and field environments.
Keywords:
camera pose estimation
rebar tying robots
feature-aware framework
structure-aware algorithms
closed-loop feedback
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