Abstract
We present NeuRIO, a streaming neural estimator for anchor-free 6-DoF relative inertial odometry using only identified inter-robot bearings, ranges, and IMU measurements. NeuRIO canonicalizes measurements into gravity-aligned coordinates, represents robots as nodes and mutual observations as factors, and uses attention for spatial reasoning and GRUs for temporal modeling. As a graph network, NeuRIO applies shared node-wise and factor-wise operators throughout the network, enabling it to handle different team sizes and time-varying observation graphs. NeuRIO is trained on a simulator that couples various motion patterns, device-level sensor characteristics, and diverse, realistic modeled, and temporally persistent sensor corruptions. In this way, NeuRIO achieves zero-shot sim-to-real transfer. Across $24$ real-world sequences, NeuRIO achieves $14.1\,\mathrm{cm}$ position RMSE and $3.9^\circ$ rotation RMSE. More importantly, NeuRIO demonstrates strong computational scalability, maintaining an update cost below $20\,\mathrm{ms}$ with up to $400$ robots in simulation, while optimization-based methods exceed $20\,\mathrm{ms}$ at only $24$ robots. Moreover, even trained on limited team sizes, NeuRIO transfers directly to unseen larger teams without architectural or parameter changes.
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Cite this article
APA 7
Li, Z., Lu, J., Ren, S., Xu, C., & Cao, Y. (2026). NeuRIO: A Streaming Neural Estimator for Zero-Shot Sim-to-Real Multi-Robot Relative Inertial Odometry. https://omanscience.com/en/articles/neurio-a-streaming-neural-estimator-for-zero-shot-sim-to-real-multi-robot-relative-inertial-odometry
MLA 9
Li, Zhehan, et al. "NeuRIO: A Streaming Neural Estimator for Zero-Shot Sim-to-Real Multi-Robot Relative Inertial Odometry." https://omanscience.com/en/articles/neurio-a-streaming-neural-estimator-for-zero-shot-sim-to-real-multi-robot-relative-inertial-odometry.
Chicago (author–date)
Li, Zhehan, Jiadong Lu, Shengwei Ren, Chao Xu, and Yanjun Cao. 2026. "NeuRIO: A Streaming Neural Estimator for Zero-Shot Sim-to-Real Multi-Robot Relative Inertial Odometry." https://omanscience.com/en/articles/neurio-a-streaming-neural-estimator-for-zero-shot-sim-to-real-multi-robot-relative-inertial-odometry.
Harvard
Li, Z., Lu, J., Ren, S., Xu, C. and Cao, Y. (2026) 'NeuRIO: A Streaming Neural Estimator for Zero-Shot Sim-to-Real Multi-Robot Relative Inertial Odometry', Available at: https://omanscience.com/en/articles/neurio-a-streaming-neural-estimator-for-zero-shot-sim-to-real-multi-robot-relative-inertial-odometry.
Vancouver
Li Z, Lu J, Ren S, Xu C, Cao Y. NeuRIO: A Streaming Neural Estimator for Zero-Shot Sim-to-Real Multi-Robot Relative Inertial Odometry. https://omanscience.com/en/articles/neurio-a-streaming-neural-estimator-for-zero-shot-sim-to-real-multi-robot-relative-inertial-odometry
IEEE
Z. Li, J. Lu, S. Ren, C. Xu, and Y. Cao, "NeuRIO: A Streaming Neural Estimator for Zero-Shot Sim-to-Real Multi-Robot Relative Inertial Odometry," https://omanscience.com/en/articles/neurio-a-streaming-neural-estimator-for-zero-shot-sim-to-real-multi-robot-relative-inertial-odometry.