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ARES OS (Autonomous Research System) is a cross-platform operating system designed to automate the scientific method. It serves as the center piece for self-driving laboratories, closing the loop between Execution (Robots/Hardware), Analysis (Sensors/AI), and Planning (Decision Algorithms).
Traditional lab automation is often rigid, scripted specifically for one machine or one experiment. ARES is designed to be:
- Modular: Swap out a planner or a device without rewriting your entire experiment.
- Cross-Platform: Runs natively on Windows, Linux, and macOS.
- Python Friendly: Core components run in high-performance C#, but you can integrate hardware and logic using Python (via PyAres).
ARES organizes your research into three main component types:
- Devices: Physical hardware interfaces (Lasers, Pumps, Furnaces) or virtual simulators.
- Analyzers: Software that processes data (Images, Logs) to determine the result of an experiment.
- Planners: Algorithms that look at previous results and decide the parameters for the next experiment.
These components come together in a Campaign, a defined workflow that runs autonomously until your research goals are met.
If you want to start running experiments, head to the user guide. Here you'll learn how to:
- Install ARES using the Launcher
- Set up your first Device
- Run your first Autonomous Campaign
If you want to extend ARES with new hardware support or custom algorithms, check out the developer guide.
- Learn the ARES Architecture
- Build a native C# Plugin
- Understand the gRPC Data Model
Download the ARES Launcher
The Official ARES Python Library
The ARES Datamodel
Report a Bug