@DanKornas: Robotics is too broad for random bookmarks. Start with a map. Awesome Robotics is a curated GitHub list of links, softw…

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Summary

Awesome Robotics is a curated GitHub list of robotics resources—simulators, libraries, papers, and more—organized by categories like simulation, ROS, ML, and perception. It's open-source under Creative Commons Attribution 4.0.

Robotics is too broad for random bookmarks. Start with a map. Awesome Robotics is a curated GitHub list of links, software libraries, papers, and other useful robotics resources. It helps you move from “what should I use?” to a shortlist by grouping robotics resources across simulation, visualization, ML, ROS, control, calibration, sensors, datasets, geometry, point clouds, and SLAM. Key features: • Simulator references – includes CoppeliaSim, AirSim, and Bullet/PyBullet for testing robot systems • ROS + robotics stack links – points to ROS, ROS 2 design docs, drivers, tracking, calibration, and robot libraries • ML for robotics – includes TensorFlow-related tools, image segmentation links, reinforcement learning resources, and robotics datasets • Mapping + perception sections – covers point clouds, geometry, visualization, and SLAM resources • Extra reading paths – links to related awesome lists, papers, and an “interesting robotics” companion list It’s open-source (Creative Commons Attribution 4.0 International license). Link in the reply
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Cached at: 06/27/26, 11:54 AM

Robotics is too broad for random bookmarks. Start with a map.

Awesome Robotics is a curated GitHub list of links, software libraries, papers, and other useful robotics resources.

It helps you move from “what should I use?” to a shortlist by grouping robotics resources across simulation, visualization, ML, ROS, control, calibration, sensors, datasets, geometry, point clouds, and SLAM.

Key features:

• Simulator references – includes CoppeliaSim, AirSim, and Bullet/PyBullet for testing robot systems • ROS + robotics stack links – points to ROS, ROS 2 design docs, drivers, tracking, calibration, and robot libraries • ML for robotics – includes TensorFlow-related tools, image segmentation links, reinforcement learning resources, and robotics datasets • Mapping + perception sections – covers point clouds, geometry, visualization, and SLAM resources • Extra reading paths – links to related awesome lists, papers, and an “interesting robotics” companion list

It’s open-source (Creative Commons Attribution 4.0 International license).

Link in the reply

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