Demonstrating Onboard Inference for Earth Science Applications with Spectral Analysis Algorithms and Deep Learning

Itai Zilberstein; Alberto Candela; Steve Chien; David Rijlaarsdam; Tom Hendrix; Leonie Buckley; Aubrey Dunne

Demonstrating Onboard Inference for Earth Science Applications with Spectral Analysis Algorithms and Deep Learning

Artificial Intelligence 2025-08-22 v1 Machine Learning

Authors: Itai Zilberstein , Alberto Candela , Steve Chien , David Rijlaarsdam , Tom Hendrix , Leonie Buckley , Aubrey Dunne

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Abstract

In partnership with Ubotica Technologies, the Jet Propulsion Laboratory is demonstrating state-of-the-art data analysis onboard CogniSAT-6/HAMMER (CS-6). CS-6 is a satellite with a visible and near infrared range hyperspectral instrument and neural network acceleration hardware. Performing data analysis at the edge (e.g. onboard) can enable new Earth science measurements and responses. We will demonstrate data analysis and inference onboard CS-6 for numerous applications using deep learning and spectral analysis algorithms.

Keywords

planetary rover autonomy remote sensing

Cite

@article{arxiv.2508.15053,
  title  = {Demonstrating Onboard Inference for Earth Science Applications with Spectral Analysis Algorithms and Deep Learning},
  author = {Itai Zilberstein and Alberto Candela and Steve Chien and David Rijlaarsdam and Tom Hendrix and Leonie Buckley and Aubrey Dunne},
  journal= {arXiv preprint arXiv:2508.15053},
  year   = {2025}
}

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International Symposium on Artificial Intelligence, Robotics and Automation in Space, November 2024

Demonstrating Onboard Inference for Earth Science Applications with Spectral Analysis Algorithms and Deep Learning

Abstract

Keywords

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