Abstract
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.
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References
Ferrari, C., Canny, J.: Planning optimal grasps. In: IEEE International Conference on Robotics and Automation (1992)
Wren, D., Fisher, R.: Dextrous hand grasping strategies using preshapes and digit trajectories. In: IEEE International Conference on Systems, Man and Cybernetics (1995)
Ciocarlie, M., Goldfeder, C., Allen, P.: Dimensionality reduction for hand-independent dexterous robotic grasping. In: International Conference on Intelligent Robots and Systems (2007)
Miller, A., Knoop, S., Christensen, H., Allen, P.: Automatic grasp planning using shape primitives. In: IEEE International Conference on Robotics and Automation (2003)
Goldfeder, C., Allen, P., Lackner, C., Pelossof, R.: Grasp planning via decomposition trees. In: IEEE International Conference on Robotics and Automation (2007)
Huebner, K., Ruthotto, S., Kragic, D.: Minimum volume bounding box decomposition for shape approximation in robot grasping. In: IEEE International Conference on Robotics and Automation (2008)
Xue, Z., Kasper, A., Zoellner, J.M., Dillmann, R.: An automatic grasp planning system for service robots. In: 14th International Conference on Advanced Robotics, ICAR (2009)
Goldfeder, C., Ciocarlie, M., Dang, H., Allen, P.K.: The columbia grasp database. In: IEEE International Conference on Robotics and Automation (2009)
Xue, Z., Zoellner, J.M., Dillmann, R.: Automatic optimal grasp planning based on found contact points. In: IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM (2008)
Miller, A., Allen, P.: Graspit! a versatile simulator for robotic grasping. IEEE Robotics & Automation Magazine (2004)
Barequet, G., Har-Peled, S.: Efficiently approximating the minimum-volume bounding box of a point set in three dimensions. J. Algorithms (2001)
Zhang, X., Redon, S., Lee, M., Kim, Y.J.: Continuous collision detection for articulated models using taylor models and temporal culling. ACM Transactions on Graphics (Proceedings of SIGGRAPH 2007) (2007)
Xue, Z., Woerner, P., Zoellner, J.M., Dillmann, R.: Efficient grasp planning using continuous collision detection. In: IEEE International Conference on Mechatronics and Automation, ICMA (2009)
Han, L., Trinkle, J., Li, Z.: Grasp analysis as linear matrix inequality problems. IEEE Transactions on Robotics and Automation (2000)
Ehmann, S.A., Lin, M.C.: Accurate and fast proximity queries between polyhedra using convex surface decomposition. In: Computer Graphics Forum (2001)
KIT ObjectModels Web Database, http://wwwiaim.ira.uka.de/ObjectModels
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Xue, Z., Dillmann, R. (2010). Efficient Grasp Planning with Reachability Analysis. In: Liu, H., Ding, H., Xiong, Z., Zhu, X. (eds) Intelligent Robotics and Applications. ICIRA 2010. Lecture Notes in Computer Science(), vol 6424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16584-9_3
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DOI: https://doi.org/10.1007/978-3-642-16584-9_3
Publisher Name: Springer, Berlin, Heidelberg
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