Awesome Robotics Resources

Free Robotics & AI learning resources, including courses, books, lectures, research papers, tutorials, projects, and more.

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AI → Robotics Transition

← Guides

If you know ML, the gaps are usually:

1. Geometry and frames. Transformations.
2. Control and dynamics. Control, kinematics & dynamics.
3. State estimation. Sensor fusion, SLAM.
4. Real-time systems. ROS 2, C++.
5. Then combine. Robot learning and embodied AI in simulation.

Robots break ML assumptions: data is sequential, actions change the data, and failure has physical cost.