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The Teachingbox uses advanced machine learning techniques to relieve developers from the programming of hand-crafted sophisticated behaviors of autonomous agents (such as robots, game players etc...) In the current status we have implemented a well founded reinforcement learning core in Java with many popular usecases, environments, policies and learners.
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RTS2 is project to create an open source environment for control of a fully autonomous observatory. It is running about dozen fully autonomous observatories. Its modular design allow easily addition of new devices (to already huge supported HW list).
A project to host code developed for the Microtransat challenge, a race between autonomous sailing robots. This project is intended for both supporting code such as tracking systems and robot control systems or parts of robot control systems.
Physically-accurate robotics simulator written in Python
ARS is a physically-accurate robotics simulator written in Python. It's main purpose is to help researchers with to develop mobile manipulators and, in general, any multi-body system. It is open-source, modular, easy to learn and use, and can be a valuable tool in the process of robot design, in the development of control and reasoning algorithms, as well as in teaching and educational activities.
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Moved to https://github.com/rdiankov/openrave
An open-source, cross-platform, plugin-based robot planning environment for autonomous robotics. Includes services like collision detection, physics, (inverse) kinematics, sensors, robot controls, python bindings, and a network scripting environment.