Skip Navigation

RoNIN: Robust Neural Inertial Navigation

Description: Dataset and pre-trained models associated with publication Herath, S., Yan, H. and Furukawa, Y., 2020, May. RoNIN: Robust Neural Inertial Navigation in the Wild: Benchmark, Evaluations, & New Methods. In 2020 IEEE International Conference on Robotics and Automation (ICRA) (pp. 3146-3152). IEEE.
Authors: Herath, Sachini; Simon Fraser University; https://orcid.org/0000-0003-2708-0509 ORCID iD
Furukawa, Yasutaka; Simon Fraser University
Yan, Hang; Washington University in St. Louis
Keywords: Inertial navigation
Trajectory
motion analysis
neural nets
neural inertial navigation
data-driven inertial navigation research
horizontal positions
IMU sensor data
ground-truth 3D trajectories
natural human motions
RoNIN
relative trajectory
body heading estimation
body facing direction
pretrained models
IMU
Field of Research: 
Computer and information sciences
>
Artificial intelligence (AI)
>
Computer vision in artificial intelligence

Computer and information sciences
>
Artificial intelligence (AI)
>
Intelligent robotics
Date: 11-Jan-2022
Publisher: Federated Research Data Repository / dépôt fédéré de données de recherche
URI: https://doi.org/10.20383/102.0543
Related Identifiers: 

This dataset is part/subset of

This dataset is part/subset of
Appears in Collections:SFU Research Data

Files in Dataset 
No files uploaded

Files for this dataset are currently being backed up so it cannot be approved at this time. Please try later.
Access to this dataset is subject to the following terms:
The RoNIN data and RoNIN pre-trained models are made available under a custom license, for non-commercial and scientific research purposes. Please see the provided LICENSE.txt file for the full terms of use.
Citation
Herath, S. , Furukawa, Y. , Yan, H. (2022) RoNIN: Robust Neural Inertial Navigation. Federated Research Data Repository. https://doi.org/10.20383/102.0543