This repo aims to calibrate Visual Place Recognition network to a target environment and provide uncertainty estimation. For more details look at our paper.

If you use the code in this repository please cite:

@ARTICLE{lajoieCalibration2022,
  author={Lajoie, Pierre-Yves and Beltrame, Giovanni},
  journal={IEEE Robotics and Automation Letters}, 
  title={Self-Supervised Domain Calibration and Uncertainty Estimation for Place Recognition}, 
  year={2023},
  volume={8},
  number={2},
  pages={792-799},
  doi={10.1109/LRA.2022.3232033}}

How to use

• Use the frame-extractor and slam_interfaces with ROS 2 to extract training samples from your data.
• Use the vpr-and-uncertainty-calibrator to calibrate your Visual Place Recognition network and train an uncertainty estimator.

See more execution details in the submodules.