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, but no such database exists. In this work we show how to automate the construction of 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.© 2009 IEEE.
CITATION STYLE
Goldfeder, C., Ciocarlie, M., Dang, H., & Allen, P. K. (2009). The columbia grasp database. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 1710–1716). https://doi.org/10.1109/ROBOT.2009.5152709
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