Autonomy in Space with Machine Learning

Autonomy in Space with Machine Learning

In the frame of the SSC/EPFL Call for Ideas 2019, Ateleris developed and implemented an autonomy algorithm for the STIX instrument that autonomously selects the optimal image data cube on-board the instrument to be sent down to the ground.

With this optimization, the image data quality can be improved tremendously, while at the same time lowering the data rate requirements by a factor of ten.

This so called Autonomous Interval Selection Algorithm had been designed by the STIX team and implemented by Ateleris in C and integrated with the STIX flight software. An external test harness helped to meet the reliability requirements and to optimize the algorithms.

Key Technologies/Terms

  • Embedded programming in C/C++
  • Parameter search and optimization

Link to our poster, we presented at the final presentation event at SSC/EPFL in January 2020.


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