GSST/CBERS-5 International Symposium on Machine Learning in Heliophysics and Space Weather

JW-ASTClaw: A Generalizable Multi-Agent Framework for Autonomous Solar Telescope Observation

Not scheduled

20m

Fernando de Mendonça - LIT (National Institute for Space Research, São José dos Campos, SP, Brazil)

Oral Instrumentation & Observational Systems Oral Contributions

Speaker

Dr Liyue Tong (National Astronomical Observatory of the Chinese Academy of Sciences)

Description

Solar observation faces complex challenges that conventional automated observation systems struggle to address, including rapidly changing weather conditions, potentially anomalous data, and the need for prompt follow-up observations of eruptive phenomena. The rapid advancement of artificial intelligence technologies offers new possibilities for tackling these challenges. This paper presents the JW-ASTClaw framework, a multi-agent system built upon Large Language Models (LLMs) and the Model Context Protocol (MCP). The system comprises three perception agents (Seeing Analyzer, Cloud Analyzer, and Sunspot & Flare Analyzer) and one execution MCP (Observation Control Middleware), all coordinated by a central decision-making agent (Reasoning Engine). The framework has been successfully deployed on Solar Full-disk Multi-layer Magnetograph (SFMM), a key instrument of Phase II of China's Meridian Project, and its effectiveness has been validated through recent observations. The design features high scalability and generality, making it applicable to other telescopes and large-scale scientific instruments.