This repository provides raw data (roll/pitch angles) of autonomous vehicles obtained from a multi-sensor array, and compared against a reference sensor. These datasets are structured to evaluate sensor fusion algorithms under varying dynamic disturbances. The sampling period was two milliseconds.
Dataset Downloads
Scenario 1: Air
Attitude estimation data captured under high dynamic aerial disturbances. Each log file contains concurrent readings from 3 IMU sensors and 1 Reference sensor.
Scenario 2: Surface
Attitude estimation data captured under aggressive surface/terrain vibrations and mechanical noise. Set of 5 independent recording sessions.
Complete Repository
Download all sensor fusion datasets, including both Air and Surface scenarios in a single compressed file.
Download All Datasets (.ZIP)
Related Publications
Real-time high-precision roll-pitch estimation of land-air vehicles using sensor fusion and improved discrete observers
Sánchez R, Edwards E. et al. (2026)
A strategy for real-time estimation using enhanced discrete generalized proportional-integral (GPI) observers.
View at ScienceDirect
Robust Sensor Fusion Using Federated Kalman Filter and Discrete GPI Observers
Sánchez Ramírez, Edwards Ernesto et al. (2024)
A robust federated Kalman filter approach for distributed systems and high-precision estimations.
View at Springer
How to Cite
@article{SanchezRamirez2026RealTime,
title={Real-time high-precision roll-pitch estimation of land-air vehicles using sensor fusion and improved discrete observers},
author={Sánchez R, Edwards E. and Rosales S, Alberto J. and Gallegos F, Francisco J. and Morales P, Carlos J. and Miranda G, Armando A.},
journal={Expert Systems with Applications},
volume={296},
pages={129052},
year={2026},
publisher={Elsevier},
doi={10.1016/j.eswa.2025.129052}
}
@article{SanchezRamirez2024Rogust,
title={Rogust Sensor Fusion Using Federated Kalman Filter and Discrete Generalized-Proportional-Integral Observers},
author={Sánchez Ramírez, Edwards Ernesto and Rosales Silva, A. J. and Ambrosio, P. J. and others},
journal={Aut. Control Comp. Sci.},
volume={58},
pages={630--641},
year={2024},
publisher={Springer},
doi={10.3103/S0146411624701104}
}