Attributions

License

Our code is licensed under the permissive MIT license to promote and foster future research and development.

Citation

If you use our work, please cite the following publication:

@article{HinesLENS2025,
  author = {Adam D. Hines  and Michael Milford  and Tobias Fischer },
  title = {A compact neuromorphic system for ultra–energy-efficient, on-device robot localization},
  journal = {Science Robotics},
  volume = {10},
  number = {103},
  pages = {eads3968},
  year = {2025},
  doi = {10.1126/scirobotics.ads3968},
  URL = {https://www.science.org/doi/abs/10.1126/scirobotics.ads3968}
}

Acknowledgements

We acknowledge continued support from the Queensland University of Technology (QUT) through the Centre for Robotics. We wish to acknowledge the support of the Research Engineering Facility (REF) team at QUT for the provision of engineering support, expertise and research infrastructure in enablement of this project. Finally, we would like to thank the organisers and participants of the 2022 Lifelong Learning at Scale topic area at the Telluride Neuromorphic Workshop for the insightful discussions and inspiring environment.

This work received funding from an ARC Laureate Fellowship FL210100156 to MM, AUSMURIB000001 associated with ONR MURI grant N00014191-2571 to MM and TF, and an ARC Discovery Early Career Researcher Award DE240100149 to TF.