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RINS-W: Robust Inertial Navigation System on Wheels

Overview

This repo contains a real-time approach for inertial navigation based only on an Inertial MeasurementUnit (IMU) for self-localizing wheeled robots. The approach builds upon two components: 1) a robust detector that uses deep neural networks to dynamically detects zero velocity; and 2) a state-of-the-art Kalman filter which incorporates this knowledge along with no lateral slip and vertical velocity as pseudo-measurements for localization.

Code

Our implementation is done in Python a Pytorch for the adapter block of the system. The code was tested under Python 3.5.

Installation & Prerequies

  1. Install pytorch. We perform all training and testing on its 1.5 version.

  2. Install required packages, e.g. with the pip3 command

pip3 install requirements.txt
  1. Clone this repo
git clone https://github.com/mbrossar/RINS-W.git

Testing

Coming soon.

Training

Coming soon.

Papers

This repo is mainly based on the paper "RINS-W: Robust Inertial Navigation System on Wheels", International Conference on Intelligent Robots and Systems (IROS), 2019 [IEEE paper, ArXiv paper]. The main differences with the paper are

  • deep neural networks only estimates when zero velocity happens.
  • deep neural networks is based on dilated convolutions and CNNs, which are much faster to train.
  • the covariance of pseudo-measurement may depends on IMU inputs.

You can also see also the paper "AI-IMU Dead-Reckoning," IEEE Transactions on Intelligent Vehicles, 2020 [IEEE paper, ArXiv paper].

Citation

If you use this code in your research, please cite:

@INPROCEEDINGS{brossard2019,
  author={M. {Brossard} and A. {Barrau} and S. {Bonnabel}},
  booktitle={2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, 
  title={{RINS-W: Robust Inertial Navigation System on Wheels}}, 
  year={2019},
  volume={},
  number={},
  pages={2068-2075},
  }

@ARTICLE{9035481,
  author={M. {Brossard} and A. {Barrau} and S. {Bonnabel}},
  journal={IEEE Transactions on Intelligent Vehicles}, 
  title={{AI-IMU Dead-Reckoning}}, 
  year={2020},
  volume={},
  number={},
  pages={},
  }

Authors

Martin Brossard*, Axel Barrau* and Silvère Bonnabel*

*MINES ParisTech, PSL Research University, Centre for Robotics, 60 Boulevard Saint-Michel, 75006 Paris, France