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1. Train robotic agents to learn pick and place with deep learning for vision-based manipulation in PyBullet. Transporter Nets, CoRL 2020.

   Python 631 106

2. Train robotic agents to learn to plan pushing and grasping actions for manipulation with deep reinforcement learning.

   Python 1.1k 328

3. Python code to fuse multiple RGB-D images into a TSDF voxel volume.

   Python 1.4k 236

4. MIT-Princeton Vision Toolbox for Robotic Pick-and-Place at the Amazon Robotics Challenge 2017 - Robotic Grasping and One-shot Recognition of Novel Objects with Deep Learning.

   Lua 325 97

5. 3DMatch - a 3D ConvNet-based local geometric descriptor for aligning 3D meshes and point clouds.

   C++ 904 187

6. MIT-Princeton Vision Toolbox for the Amazon Picking Challenge 2016 - RGB-D ConvNet-based object segmentation and 6D object pose estimation.

   C++ 309 140