Automatic grasp planning using shape primitives Export

@proceedings{citeulike:1247706, abstract = {Automatic grasp planning for robotic hands is a difficult problem because of the huge number of possible hand configurations. However, humans simplify the problem by choosing an appropriate prehensile posture appropriate for the object and task to be performed. By modeling an object as a set of shape primitives, such as spheres, cylinders, cones and boxes, we can use a set of rules to generate a set of grasp starting positions and pregrasp shapes that can then be tested on the object model. Each grasp is tested and evaluated within our grasping simulator "GraspIt!", and the best grasps are presented to the user. The simulator can also plan grasps in a complex environment involving obstacles and the reachability constraints of a robot arm.}, author = {Miller, A. T. and Knoop, S. and Christensen, H. I. and Allen, P. K.}, booktitle = {Robotics and Automation, 2003. Proceedings. ICRA '03. IEEE International Conference on}, citeulike-article-id = {1247706}, citeulike-linkout-0 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1241860}, journal = {Robotics and Automation, 2003. Proceedings. ICRA '03. IEEE International Conference on}, keywords = {choice\_of\_grasp, hum-rob-mapping}, pages = {1824--1829 vol.2}, posted-at = {2009-01-08 10:20:51}, priority = {0}, title = {Automatic grasp planning using shape primitives}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1241860}, volume = {2}, year = {2003} }

TY - CONF ID - citeulike:1247706 L3 - citeulike-article-id:1247706 N2 - Automatic grasp planning for robotic hands is a difficult problem because of the huge number of possible hand configurations. However, humans simplify the problem by choosing an appropriate prehensile posture appropriate for the object and task to be performed. By modeling an object as a set of shape primitives, such as spheres, cylinders, cones and boxes, we can use a set of rules to generate a set of grasp starting positions and pregrasp shapes that can then be tested on the object model. Each grasp is tested and evaluated within our grasping simulator "GraspIt!", and the best grasps are presented to the user. The simulator can also plan grasps in a complex environment involving obstacles and the reachability constraints of a robot arm. JF - Robotics and Automation, 2003. Proceedings. ICRA '03. IEEE International Conference on EP - 1829 vol.2 TI - Automatic grasp planning using shape primitives VL - 2 T2 - Robotics and Automation, 2003. Proceedings. ICRA '03. IEEE International Conference on SP - 1824 KW - choice_of_grasp KW - hum-rob-mapping AU - Miller, AT AU - Knoop, S AU - Christensen, HI AU - Allen, PK PY - 2003/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1241860 ER -