Continuous collision detection for articulated models using Taylor models and temporal culling
ACM SIGGRAPH 2007 papers
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
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Grasping can be seen as two steps: placing the hand at a grasping pose and closing the fingers. In this paper, we introduce an efficient algorithm for grasping pose generation. Depend on the hand kinematic, boxes of different sizes are sampled. The reachability for graping is represented by the information, from where the hand can grasp the box firmly. These boxes represent real objects, which at run-time will be decomposed into such boxes, so that the grasping poses for the real object can be generated. Concrete grasps at a grasping pose will be further checked for its grasp quality. Real experiments with two different robotic hands show the efficiency and feasibility of our method.