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The AIKO orbital_OLIVER is a software ecosystem to enable autonomous spacecraft operations onboard the satellite thereby improving its performance.

It is an AI-based software solution conceived for satellite owners and operators and intended for streamlining spacecraft operations, augmenting mission performance, and reducing the costs of operations.

Through a modular architecture, orbital_OLIVER enables onboard autonomy based on a three-stage autonomous pipeline:

  1. Platform and environment sensing,
  2. Reasoning and goal definition,
  3. Planning and scheduling.

With orbital_OLIVER, satellites can carry out complex endeavours such as timely data analysis, payload product optimization, and automated platform diagnostics and prognostics.

This supports satellite operators in the mission control centre with optimal and rapid decision-making, allowing ground control to focus on high-level, strategic decisions.

By design, orbital_OLIVER is customizable to handle several mission scenarios, making it a suitable operations orchestrator in remote sensing, telecommunications, and scientific applications.

While the core algorithms stay unchanged, this configurability is allowed by flexible interfaces (in compliance with ECSS and CCSDS standards), and by a tailorable knowledge-base to specify mission rules.

The product has been successfully bench-tested on a variety of commercial off-the-shelf (COTS) computational platforms with different hardware architectures (32-bit ARMv7, 64-bit ARMv8, 64-bit x86), providing extra flexibility with respect to the system requirements of the spacecraft.

The development and validation of orbital_OLIVER is currently backed by ESA through the InCubed+ program, which will lead the product to TRL9 certification by 2023.

Currently assessed at TRL7, orbital_OLIVER will have its maiden flight in 2022, while four additional missions will test its features throughout 2023.

Commercialization will start in 2024, but early access will be provided to selected customers who want to improve the efficiency of their operations pipeline.

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Last updated: 2022-07-26




lead time
6 mo


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