Skip to content
/ ATLeS Public

An inexpensive, open-source system for automated, high-throughput, realtime observation and conditioning experiments.

License

Notifications You must be signed in to change notification settings

liffiton/ATLeS

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

ATLeS: Automated Tracking and Learning System

The goal of the ATLeS project is to create an inexpensive, open-source system for automated, high-throughput, realtime observation and conditioning experiments. Zebrafish, danio rerio, are the target organism for the initial design.

ATLeS consists of one or more ATLeS boxes, each of which can run an automated experiment on a single organism at a time, and a separate server that provides a combined interface for managing and controlling all of the boxes and their experiments in one place. Each box uses an inexpensive Raspberry Pi as its "brain," an infrared-sensitive camera as its "eyes," and inexpensive materials for the structure. A central server can connect to boxes over a network (ethernet or wifi) to control and manage them via a web interface. The server software is written in Python, and it runs under Linux, OS X, or Windows.

Please visit the main ATLeS website or look in the docs folder for more details and documentation.

Authors

ATLeS was created by Mark Liffiton and Brad Sheese at Illinois Wesleyan University.

Open-Source Licenses

Each part of the ATLeS project is licensed under one of two open-source licenses, depending on what type of material it is. See docs/licenses.md for details.

About

An inexpensive, open-source system for automated, high-throughput, realtime observation and conditioning experiments.

Resources

License

Stars

Watchers

Forks

Packages

No packages published