Robotics - Grasping
Books
- Murray et al: A Mathematical Introduction to Robotic Manipulation (1994)
Talks
- MIT Robotics - Ken Goldberg - The New Wave in Robot Grasping (2020)
- FALL 2021 GRASP on Robotics - Dieter Fox, University of Washington
- MIT Robotics - Dieter Fox - Toward Foundational Robot Manipulation Skills (2023)
Surveys
- J.Bohng et al: Data-driven grasp synthesis—a survey (2016)
- H. Zhang el al: Robotic Grasping from Classical to Modern: A Survey (2022)
Simulators
- A. Miller, P. Allen: GraspIt - A Versatile Simulator for Robotics Grasping (2004), web, github
Workshops
Grasp Datasets
- ARMBench: An Object-centric Benchmark Dataset for Robotic Manipulation (2023), web
- GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping (2020)
- 190 cluttered and complex scenes
- 97,280 RGB-D image with over one billion grasp poses
- Captured with Microsoft KinectAzure and RealSense D435
- https://graspnet.net/
- Columbia Grasp database
- VisGraB
- Playpen data set
- Cornell Grasping Dataset
- Deep Learning for Detecting Robotics Grasps (2014)
- Contains 885 RGB-D images of real objects, with 5110 human-labelled positive and 2909 negative grasps
- Relatively small when compared with synthetic datasets
State of the art
- K. Goldberg et al, Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics (2017)
- D. Morrison, J. Leitner, and P. Corke, Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach (2018), github
- D. Fox et al, 6-DOF GraspNet: Variational Grasp Generation for Object Manipulation (2019)
- D. Fox et al, Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes (2021), video, github