grasping.cs.columbia.edu
Columbia Robotics | CVGC | Peter K. Allen  

Welcome to the Dexterous Grasping page of the Columbia University Robotics Group, part of the Columbia Department of Computer Science. This page showcases our groups work in the area of grasp planning and manipulation for robotic and prosthetic hands.

Downloads


The Columbia Grasp Database, (Video) a large dataset of precomputed grasps on thousands of 3D models, is available for download as a PostgreSQL database backup file (70M). To download the database, please send an email to columbiarobotics@gmail.com with your name and university or company affiliation. You will recieve the link in your email. The CGDB is intended to be used with GraspIt! and the GraspIt! manual contains details on installing and using it. To use the database, you will also need to download the Princeton Shape Benchmark, which contains the 3D models used in the database. There is a known issue with the alignments of some database models to each other which will be fixed in the next GraspIt! update.


GraspIt!, our robotic grasping simulation tool, is available for download here.


Funded in part by NSF Award 0904514

Selected Publications

For a complete list of our group's publications, including those not about dexterous grasping, please visit our home page.

Corey Goldfeder, Matei Ciocarlie, Jaime Peretzman, Hao Dang, Peter K. Allen, Data-Driven Grasping with Partial Sensor Data, International Conference on Intelligent Robots and Systems, 2009.

Matei Ciocarlie, Peter K. Allen, Design and Analysis Tool for Underactuated Compliant Hands, International Conference on Intelligent Robots and Systems, 2009.

Matei Ciocarlie, Peter K. Allen, Hand Posture Subspaces for Dexterous Robotic Grasping, International Journal of Robotics Research, 2009, vol. 28.

Corey Goldfeder, Matei Ciocarlie, Hao Dang, Peter K. Allen, The Columbia Grasp Database, International Conference on Robotics and Automation, 2009. Video.

Matei Ciocarlie, Hao Dang, Jamie Lukos, Marco Santello, Peter K. Allen, Functional Analysis of Finger Contact Locations during Grasping, Eurohaptics, 2009.

Matei Ciocarlie, Samuel T. Clanton, M. Chance Spalding, Peter K. Allen, Biomimetic Grasp Planning for Cortical Control of a Robotic Hand, International Conference on Intelligent Robots and Systems, 2008.

Matei Ciocarlie, Peter K. Allen, On-Line Interactive Dexterous Grasping, Eurohaptics, 2008. Video.

Matei Ciocarlie, Corey Goldfeder, Peter K. Allen, Dimensionality Reduction for Hand-Independent Dexterous Robotic Grasping, International Conference on Intelligent Robots and Systems, 2007.

Corey Goldfeder, Peter K. Allen, Claire Lackner, Raphael Pelossof, Grasp Planning via Decomposition Trees, International Conference on Robotics and Automation, 2007.

Matei Ciocarlie, Claire Lackner, Peter K. Allen, Soft finger model with adaptive contact geometry for grasping and manipulation tasks, IEEE Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2007.

Matei Ciocarlie, Andrew Miller, Peter K. Allen, Grasp Analysis Using Deformable Fingers, International Conference on Intelligent Robots and Systems, 2005.

Andrew Miller, Peter K. Allen, V. Santos, F. Valero-Cuevas, From Robot Hands to Human Hands: A Visualization and Simulation Engine for Grasping Research, Industrial Robot 32:1, 2005.

Andrew Miller, Peter K. Allen, Graspit! A Versatile Simulator for Robotic Grasping, IEEE Robotics and Automation Magazine 11:4, 2004.

Andrew Miller, Peter K. Allen, V. Santos, F. Valero-Cuevas, From Robot Hands to Human Hands: A Visualization and Simulation Engine for Grasping Research, International Conference on Intelligent Manipulation and Grasping, 2004.

Rafael Pelossof, Andrew Miller, Peter Allen, Tony Jebara, An SVM Learning Approach to Robotic Grasping, International Conference on Robotics and Automation, 2004.

Andrew T. Miller, Steffen Knoop, Henrik I. Christensen, Peter K. Allen, Automatic Grasp Planning using Shape Primitives, International Conference on Robotics and Automation, 2003.

Columbia Vision and Graphics Center