Astronomy16 papers
Artificial Intelligence and Machine Learning in Planetary Science
A companion collection for the ACM 2026 talk by Valerio Carruba
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Valerio Carruba
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Remote Agent: to boldly go where no AI system has gone before
Muscettola, Nicola et al. (1998)
- Published
- Aug 1, 1998
- Journal
- Artificial Intelligence · Vol. 103 · No. 1-2
- DOI
- 10.1016/S0004-3702(98)00068-X
At a GlanceAI
Remote Agent showed how an autonomous AI system could manage a spacecraft under real mission conditions.
SummaryAI
This paper is important because it demonstrated a practical AI system capable of autonomous spacecraft control, a major step beyond laboratory prototypes. From the title and publication context, the work centers on Remote Agent, a system designed to operate in demanding, remote environments where human intervention is limited. Its significance lies in showing that AI planning and execution could be trusted in real-world space operations, helping pave the way for more capable autonomous missions.
Method SnapshotAI
The paper presents an autonomous agent architecture for spacecraft planning, execution, and control.
BackgroundAI
Familiarity with artificial intelligence, autonomous agents, and basic spacecraft operations is helpful.
A landmark paper in autonomous spacecraft operations, this work demonstrated that AI planning and execution systems could reliably control a spacecraft in a real mission environment. By validating the Remote Agent architecture beyond laboratory experiments, it established a foundation for autonomous space exploration and remains an essential reference for researchers interested in AI-driven mission planning, spacecraft autonomy, and intelligent control.
— VC