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

• URL: http://arxiv.org/abs/2601.11394v1
• Date: Fri, 16 Jan 2026 16:06:32 GMT
• Title: The Mini Wheelbot Dataset: High-Fidelity Data for Robot Learning
• Abstract summary: This paper introduces a comprehensive dynamics dataset for the Mini Wheelbot, an open-source, quasi-symmetric balancing reaction wheel unicycle.<n>The dataset provides 1 kHz synchronized data encompassing all onboard sensor readings, state estimates, ground-truth poses from a motion capture system, and third-person video logs.
• Score: 11.872449230532501
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The development of robust learning-based control algorithms for unstable systems requires high-quality, real-world data, yet access to specialized robotic hardware remains a significant barrier for many researchers. This paper introduces a comprehensive dynamics dataset for the Mini Wheelbot, an open-source, quasi-symmetric balancing reaction wheel unicycle. The dataset provides 1 kHz synchronized data encompassing all onboard sensor readings, state estimates, ground-truth poses from a motion capture system, and third-person video logs. To ensure data diversity, we include experiments across multiple hardware instances and surfaces using various control paradigms, including pseudo-random binary excitation, nonlinear model predictive control, and reinforcement learning agents. We include several example applications in dynamics model learning, state estimation, and time-series classification to illustrate common robotics algorithms that can be benchmarked on our dataset.

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