antoalli/L2G
End-to-End Learning to Grasp from Object Point Clouds
This project helps roboticists program industrial robots to pick up various objects effectively. It takes 3D scans (point clouds) of objects as input and outputs precise instructions (6-DOF grasps) for a parallel-jaw robotic gripper, telling it exactly where and how to grasp. This is for robotics engineers and researchers working on automation and object manipulation tasks.
No commits in the last 6 months.
Use this if you need a robust way for robots to determine optimal grasping points on diverse objects based purely on their 3D shape, without prior geometric assumptions.
Not ideal if you are working with non-parallel-jaw grippers or require extremely fast, real-time grasp generation on embedded systems with limited computational power.
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43
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7
Language
Python
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Last pushed
Apr 24, 2024
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