DLO-Splatting: Tracking Deformable Linear Objects Using 3D Gaussian Splatting

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.

@article{dinkel2025_2505.08644,
  title={ DLO-Splatting: Tracking Deformable Linear Objects Using 3D Gaussian Splatting },
  author={ Holly Dinkel and Marcel Büsching and Alberta Longhini and Brian Coltin and Trey Smith and Danica Kragic and Mårten Björkman and Timothy Bretl },
  journal={arXiv preprint arXiv:2505.08644},
  year={ 2025 }
}