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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; ORCID iD
Furukawa, Yasutaka; Simon Fraser University
Yan, Hang; Washington University in St. Louis
Keywords: Inertial navigation
motion analysis
neural nets
neural inertial navigation
data-driven inertial navigation research
horizontal positions
IMU sensor data
ground-truth 3D trajectories
natural human motions
relative trajectory
body heading estimation
body facing direction
pretrained models
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
Related Identifiers: 

This dataset is part/subset of

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

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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.
Herath, S. , Furukawa, Y. , Yan, H. (2022) RoNIN: Robust Neural Inertial Navigation. Federated Research Data Repository.