# Earth observation satellites

Published articles for Earth observation satellites.

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## Large Language Model-Assisted Adaptive Heuristic Search for Agile Earth Observation Satellite Scheduling

DevFeed: [Large Language Model-Assisted Adaptive Heuristic Search for Agile Earth Observation Satellite Scheduling](<https://devfeed.tech/articles/large-language-model-assisted-adaptive-heuristic-search-for-agile-earth-observation-satellite-scheduling-117486.md>)

Original publisher: [Read original article](<https://arxiv.org/abs/2611.04458>)

Author: He Wang, Yeye Liu, Ruijie Li, Xuemei Jiang, Junyu Wu, Lining Liu Zhuoqi Man, Tao Li, Yanjie Song

Published: 2026-11-04T05:00:00Z

Content type: article

Language: en

Sources: [arXiv: Artificial Intelligence](<https://devfeed.tech/sources/arxiv-artificial-intelligence.md>)

Topics: [scheduling](<https://devfeed.tech/topics/scheduling.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>)

Tags: [adaptive](<https://devfeed.tech/tags/adaptive.md>), [agile](<https://devfeed.tech/tags/agile.md>), [cs-ai](<https://devfeed.tech/tags/cs-ai.md>), [cs-cl](<https://devfeed.tech/tags/cs-cl.md>), [earth](<https://devfeed.tech/tags/earth.md>), [earth-observation-satellites](<https://devfeed.tech/tags/earth-observation-satellites.md>), [energy](<https://devfeed.tech/tags/energy.md>), [experiments](<https://devfeed.tech/tags/experiments.md>), [imaging](<https://devfeed.tech/tags/imaging.md>), [language](<https://devfeed.tech/tags/language.md>), [language-model](<https://devfeed.tech/tags/language-model.md>), [large-language-model](<https://devfeed.tech/tags/large-language-model.md>), [llm](<https://devfeed.tech/tags/llm.md>), [satellite](<https://devfeed.tech/tags/satellite.md>), [scheduling](<https://devfeed.tech/tags/scheduling.md>), [search](<https://devfeed.tech/tags/search.md>)

### AI overview

The method combines an LLM with ant colony search to schedule agile satellite imaging under observation-window, maneuvering, and energy constraints. The LLM creates an instance-specific initial task-selection heuristic; search performance and scheduling information then feed back into the LLM to refine it. Proposed changes are tested through paired solution constructions before entering the search. A unified procedure handles task selection, satellite assignment, and observation timing. Across six scenarios with 50-200 imaging tasks, the method achieved 4.3%-9.6% higher mean observation benefit than the strongest baseline.

### Source excerpt

arXiv:2611.04458v1 Announce Type: new Abstract: Agile Earth observation satellites must coordinate imaging tasks within limited observation windows, while accounting for attitude maneuvering and onboard energy constraints. Competition among observation opportunities makes scheduling performance sensitive to the heuristic rules used for task selection. This letter proposes a large language model (LLM)-assisted adaptive heuristic search method for agile Earth observation satellite scheduling. The LLM generates an initial heuristic rule according to the characteristics of the scheduling instance. During the subsequent ant colony search, search performance and scheduling information are fed back to the LLM to refine the heuristic rule. The proposed modifications are evaluated through paired solution constructions before being incorporated into the search process. A unified scheduling procedure determines task selection, satellite assignment, and observation timing under the operational constraints. Experiments on six scheduling scenarios involving 50--200 imaging tasks demonstrate that the proposed method achieves 4.3\%--9.6\% higher mean observation benefit than the strongest baseline.