From Isolated Instruments to an Autonomous Research System
Legacy labs rely on manual transfers and disconnected controllers. ARES OS 2.0 transforms standalone hardware into an integrated, digitalized lab ecosystem.
Universal Device Control
Integrate legacy sensors and modern hardware without the fear of proprietary software lock-in, streamlined by our Python library PyAres.
Autonomous Execution
Eliminate data collection bottlenecks with automated multi-step experimental runs designed for safe, closed-loop execution.
Centralized Data Management
Ingest, monitor, and archive raw experiment metrics automatically in real time across all connected laboratory modules.
Power Closed-Loop Autonomous Experimentation
Pair physical instruments with machine learning planners and custom analysis routines to allow your experiments to self-optimize in real time.
Modular Software Architecture
Decoupled services engineered for high performance, language flexibility, and scale.
| Component | Technology | Role in System |
|---|---|---|
| ARES Core | ASP.NET Core / C# | Coordinates hardware, planners, and analyzers; orchestrates workflows and manages database interactions. |
| ARES Datamodel | gRPC & Protobuf | Fast, language-agnostic streaming across distributed lab devices packaged as a version controlled datamodel. |
| PyAres | Python | Lightweight Python interface for researchers to rapidly prototype devices, planners and analyzers. |
| ARES UI | Blazor Web UI | Web-based UI for real-time visual monitoring, device status, and manual overrides. |
Ready to Automate Your Lab?
Set up ARES OS 2.0 in minutes using the official ARES Launcher, or clone the repository to start developing custom hardware drivers.
Clone the Repository:
git clone https://github.com/AFRL-ARES/ARES.gitPublications & Research
Read some of our publications and preprints to learn how ARES OS is driving the next generation of scientific research.