The Mini Wheelbot Dataset: High-Fidelity Data for Robot Learning (Dataset)

Wheelbot Dataset

A large, high-quality dynamics dataset of the [Mini Wheelbot](https://github.com/wheelbot/Mini-Wheelbot). The dataset contains 1 kHz data of all onboard sensor readings, the estimated state, ground-truth pose measurements from a motion capture system, and a third-person view video of the experiment. We perform a variety of experiments using pseudo-random binary excitation signals (PRBS) as setpoints of a linear controller, an MPC for driving, and an RL policy that races along a track. Experiments are performed across multiple hardware instances and on different surfaces. With this dataset, we hope to encourage researchers to use the Mini Wheelbot to benchmark their learning-based control methods, even without access to the real hardware. We include two example implementations of how to use the dataset, i.e., for dynamics learning and state estimation. A detailled description of this dataset is available in the brief on arxiv.

If you find this dataset helpful, please cite the Mini Wheelbot paper and/or dataset directly:

```bibtex

@inproceedings{hose2025mini,

title={The {Mini Wheelbot}: A Testbed for Learning-based Balancing, Flips, and Articulated Driving},

booktitle={2025 IEEE International Conference on Robotics and Automation (ICRA)},

publisher={IEEE},

author={Hose, Henrik and Weisgerber, Jan and Trimpe, Sebastian},

year={2025},

}

@article{hose2026dataset,

title={The {Mini Wheelbot} Dataset: High-Fidelity Data for Robot Learning},

author={Henrik Hose and Paul Brunzema and Devdutt Subhasish and Sebastian Trimpe},

year={2026},

url={https://arxiv.org/abs/2601.11394},

}

```