DLO-Splatting: Tracking Deformable Linear Objects Using 3D Gaussian Splatting
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913850593378304 |
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| author | Dinkel, Holly Büsching, Marcel Longhini, Alberta Coltin, Brian Smith, Trey Kragic, Danica Björkman, Mårten Bretl, Timothy |
| author_facet | Dinkel, Holly Büsching, Marcel Longhini, Alberta Coltin, Brian Smith, Trey Kragic, Danica Björkman, Mårten Bretl, Timothy |
| contents | This work presents DLO-Splatting, an algorithm for estimating the 3D shape of Deformable Linear Objects (DLOs) from multi-view RGB images and gripper state information through prediction-update filtering. The DLO-Splatting algorithm uses a position-based dynamics model with shape smoothness and rigidity dampening corrections to predict the object shape. Optimization with a 3D Gaussian Splatting-based rendering loss iteratively renders and refines the prediction to align it with the visual observations in the update step. Initial experiments demonstrate promising results in a knot tying scenario, which is challenging for existing vision-only methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_08644 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | DLO-Splatting: Tracking Deformable Linear Objects Using 3D Gaussian Splatting Dinkel, Holly Büsching, Marcel Longhini, Alberta Coltin, Brian Smith, Trey Kragic, Danica Björkman, Mårten Bretl, Timothy Computer Vision and Pattern Recognition Robotics This work presents DLO-Splatting, an algorithm for estimating the 3D shape of Deformable Linear Objects (DLOs) from multi-view RGB images and gripper state information through prediction-update filtering. The DLO-Splatting algorithm uses a position-based dynamics model with shape smoothness and rigidity dampening corrections to predict the object shape. Optimization with a 3D Gaussian Splatting-based rendering loss iteratively renders and refines the prediction to align it with the visual observations in the update step. Initial experiments demonstrate promising results in a knot tying scenario, which is challenging for existing vision-only methods. |
| title | DLO-Splatting: Tracking Deformable Linear Objects Using 3D Gaussian Splatting |
| topic | Computer Vision and Pattern Recognition Robotics |
| url | https://arxiv.org/abs/2505.08644 |