Data · dataset · 2026
Vision-Language Agents for Active Perception in Optics Laboratories
Listed in ZivaHub and Deakin Research Online and DMU Figshare — shown once because both records carry DOI 10.48550/arxiv.2609.32918
Vision-language models (VLMs) are increasingly being used in scientific workflows, but their ability as agents to directly control laboratory experiments from visual feedback remains underexplored.
Description
This capability is important because many laboratory tasks do not naturally provide dense, pre-defined numerical objectives: informative signals can be sparse, intermittent, or visually ambiguous. A more general laboratory agent should instead be able to interpret visual observations, take actions to acquire useful feedback, and adapt its behavior based on the consequences of those actions.
We study whether general-purpose VLMs can perform this kind of closed-loop scientific control using experimental optics as a testbed. We evaluate agents on three experimental systems that isolate distinct capabilities: a Michelson interferometer, a two-mirror cavity, and a four-mirror optical relay. The agents observe camera images, directly issue actuator and measurement commands, and retain their interaction history without receiving an engineered scalar objective during control.
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Across these experiments and matched simulations, we find that, given task-specific natural-language guidance, VLMs can estimate actuator-response relationships, resolve ambiguous observations through intervention, and actively create informative visual feedback when signals are sparse. These results suggest that pretrained multimodal models can serve as important decision-making agents within the experimental loop. Our work also establishes optics as a physically grounded testbed for visual reasoning and active perception in scientific agents.
Links
Where it is published
- DOI doi.org/10.48550/arxiv.2609.32918 ↗
DOI / persistent id · from zivahub uct ac za
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from zivahub uct ac za
Topics
- From keywords
- Computer Science & AI · Computer Science & AI · Computer Science & AI · Earth & Environmental Science · Earth & Environmental Science · Earth & Environmental Science · Physics · Physics · Physics
- Inferred from text
- Artificial intelligence 69% · Image 65%
Provenance · 3 source records, 16 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ZivaHub | oai:figshare.com:article/34033608 | 11 d ago | JSON v1 |
| Deakin Research Online | oai:figshare.com:article/34033608 | 11 d ago | JSON v1 |
| DMU Figshare | oai:figshare.com:article/34033608 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].anzsrc:group:4602 | enrichment · zivahub uct ac za | taxonomy-embedding@1.1.0 | title+keywords+description (69%) |
| concepts[field].local:field:computer-science-ai | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · figshare dmu ac uk | connector:figshare_dmu_ac_uk@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · figshare dmu ac uk | connector:figshare_dmu_ac_uk@1.0.0 | |
| concepts[field].local:field:physics | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
| concepts[field].local:field:physics | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:physics | mapping · figshare dmu ac uk | connector:figshare_dmu_ac_uk@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · zivahub uct ac za | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/description |
| license | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/rights |
| publication_date | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| title | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/title |