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

Detect 6-DOF grasp poses in point clouds

Summary of key papers and blogs about diffusion models to learn about the topic. Detailed list of all published diffusion robotics papers.

Generative Grasping CNN from "Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach" (RSS 2018)

Baseline model for "GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping" (CVPR 2020)

Antipodal Robotic Grasping using GR-ConvNet. IROS 2020.

A curated list of 3D Vision papers relating to Robotics domain in the era of large models i.e. LLMs/VLMs, inspired by awesome-computer-vision, including papers, codes, and related websites

Deep Reinforcement Learning for Robotic Grasping from Octrees

Python module for GQ-CNN training and deployment with ROS integration.

[ICRA 2022] CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation

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.

GRAB: A Dataset of Whole-Body Human Grasping of Objects

Pytorch implementation of diffusion models on Lie Groups for 6D grasp pose generation https://sites.google.com/view/se3dif/home

Detecting robot grasping positions with deep neural networks. The model is trained on Cornell Grasping Dataset. This is an implementation mainly based on the paper 'Real-Time Grasp Detection Using Convolutional Neural Networks' from Redmon and Angelova.

GrabNet: A Generative model to generate realistic 3D hands grasping unseen objects (ECCV2020)

paper list of robotic grasping and some related works

An implementation of our RA-L work 'Real-world Multi-object, Multi-grasp Detection'

Multi-Viewpoint Picking (ICRA 2019)

Toolbox for our GraspNet-1Billion dataset.

The GraspIt! simulator