ripl-articulation 2025.10.20

Package containing the articulation estimation tools of the RIPL Lab of the University of Waterloo.

The RIPL Lab Articulation Estimation Tools

Authors: Russell Buchanan, Adrian Röfer

This package contains the implementation of the articulation estimators described in:

• "Online estimation of articulated objects with factor graphs using vision and proprioceptive sensing", Buchanan et al., ICRA 2024. ArXiv.

Installation

Simply install the package from PyPi as

pip install ripl_articulation

Usage

The core functionality is estimating an SE3 articulation from a series of SE3 pose pairs like so:

from ripl_articulation import solve_articulation_from_poses

# Poses of Frame A in some reference frame
ref_T_A = ...
# Poses of Frame B in some reference frame
ref_T_B = ...

Xi, thetas = solve_articulation_from_poses(ref_T_A, ref_T_B)

From the solution we can reconstruct B as ref_T_B = ref_T_A @ exp(Xi * thetas), where exp is your favorite SE3 exponential map implementation.

Further, the package provides the individual articulation factor RelativePoseFactor which can be added to a gtsam factor graph. It can simply be imported as from ripl_articulation import RelativePoseFactor.

In addition to these core functionalities of the paper, the package includes a utils package, which implements a discrete ground truth articulation container, i.e. Articulation, and distance metrics to compare solved articulations to it.

Citing the Package

If you use or compare to this estimator, please cite our work as

@inproceedings{buchanan2024online,
  title={Online estimation of articulated objects with factor graphs using vision and proprioceptive sensing},
  author={Buchanan, Russell and R{\"o}fer, Adrian and Moura, Jo{\~a}o and Valada, Abhinav and Vijayakumar, Sethu},
  booktitle={2024 IEEE International Conference on Robotics and Automation (ICRA)},
  pages={16111--16117},
  year={2024},
  organization={IEEE}
}