Joint optimization of bundle adjustment and point cloud registration produces dense 3D reconstructions with 2.7 mm average accuracy and 70 points per cm² resolution while outperforming prior extrinsic calibration methods.
A new technique for fully autonomous and efficient 3d robotics hand/eye calibration
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.RO 2years
2019 2verdicts
UNVERDICTED 2representative citing papers
A precision pollination robot achieves 93.1% flower detection accuracy and 76.9% pollination success rate on high-fidelity artificial flowers.
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A Joint Optimization Approach of LiDAR-Camera Fusion for Accurate Dense 3D Reconstructions
Joint optimization of bundle adjustment and point cloud registration produces dense 3D reconstructions with 2.7 mm average accuracy and 70 points per cm² resolution while outperforming prior extrinsic calibration methods.
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Flower Interaction Subsystem for a Precision Pollination Robot
A precision pollination robot achieves 93.1% flower detection accuracy and 76.9% pollination success rate on high-fidelity artificial flowers.