Collecting grasp data for learning and benchmarking
purposes is very expensive. It would be helpful to
have a standard database of graspable objects, along with a set
of stable grasps for each object,. We have constructed
a database consisting of several hands, thousands of objects,
and hundreds of thousands of grasps. Using this database, we
demonstrate a novel grasp planning algorithm that exploits
geometric similarity between a 3D model and the objects in the
database to synthesize form closure grasps. Our contributions
are this algorithm, and the database itself, which we are
releasing to the community as a tool for both grasp planning
and benchmarking. related paper: The Columbia Grasp Database
Corey Goldfeder, Matei Ciocarlie, Hao Dang and Peter K. Allen, ICRA 2009
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