camera-fdir

Camera FDIR Plugin

This module contains a sample plugin implementation of the ExpectedLabels interface that replicates the OrbitAI experiment.

Sample Requests

The Camera FDIR Plugin is used to train a model in the 6D input space using as training data the photodiode measurements captured at each surface of the spacecraft. The following API request is invoked to enable the training data feed subscription:

http://<SUPERVISOR_HOST>:<APP_PORT>/api/v1/training/data/subscribe

The labelsPlugin payload property is set to the CameraStateLabels extension point implementation in the CameraFdirPlugin plugin class to determine and return the expected labels:

{
  "expId": 1,
  "datasetId": 1,
  "iterations": 1800,
  "interval": 2,
  "labelsPlugin": "esa.mo.nmf.apps.saasyml.plugins.CameraFdirPlugin.CameraStateLabels",
  "params": ["CADC0884", "CADC0886", "CADC0888", "CADC0890", "CADC0892", "CADC0894"]
}

References

The following are references to the OrbitAI experiment.

Plain Text

Labrèche, G., Evans, D., Marszk, D., Mladenov, T., Shiradhonkar, V., Soto, T., & Zelenevskiy, V. (2022). OPS-SAT Spacecraft Autonomy with TensorFlow Lite, Unsupervised Learning, and Online Machine Learning. 2022 IEEE Aerospace Conference (AERO), 2022, pp. 1-17, doi: 10.1109/AERO53065.2022.9843402.

BibTex

@INPROCEEDINGS{9843402,
  author={Labrèche, Georges and Evans, David and Marszk, Dominik and Mladenov, Tom and Shiradhonkar, Vasundhara and Soto, Tanguy and Zelenevskiy, Vladimir},
  booktitle={2022 IEEE Aerospace Conference (AERO)},
  title={{OPS-SAT Spacecraft Autonomy with TensorFlow Lite, Unsupervised Learning, and Online Machine Learning}},
  year={2022},
  volume={},
  number={},
  pages={1-17},
  doi={10.1109/AERO53065.2022.9843402}}