A hybrid approach for grasping 3D objects

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009

Volumn , Issue , 2009, Pages 1272-1277

  Sahbani, Anis ^a   El Khoury, Sahar ^b  

^a UNIVERSITÉ PIERRE ET MARIE CURIE   (France)

^b UPMC UNIV PARIS 06   (France)

Author keywords

[No Author keywords available]

Indexed keywords

3D OBJECT; ANALYTICAL METHOD; CONTACT POINTS; HYBRID APPROACH; NOVEL STRATEGIES; ROBOTIC HANDS;

INTELLIGENT ROBOTS;

END EFFECTORS;

EID: 76249120410     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IROS.2009.5354105     Document Type: Conference Paper

References (31)

1. A.T. Miller, GraspIt!: A Versatile Simulator for Robotic Grasping, PhD thesis, 2001.
2. D.J. Montana, The condition for contact grasp stability, in Proc. IEEE Int. Conf. Robot. Automat., pp. 412-417, 1991.
3. R.M. Murray, Z. Li, and S.S. Sastry, A Mathematical introduction to robotic manipulation, Orlando, FL: CRC, 1994.
4. J.K. Salisbury and B. Roth, Kinematic and force analysis of articulated hands, ASME J. Mech., Transmissions, Automat., Design, vol. 105, pp. 33-41, 1982.
5. W.S. Howard and V. Kumar, On the stability of grasped objects, IEEE Transactions on Robotics and Automation, vol. 12(6), pp. 904917, 1996.
6. Ch. Borst, M. Fischer and G. Hirzinger, Grasp Planning: How to Choose a Suitable Task Wrench Space, In Proceedings of IEEE International Conference on Robotics and Automation, 2004.
7. M. Prats, P.J. Sanz and A.P. del Pobil, Task-Oriented Grasping using Hand Preshapes and Task Frames, In Proceedings of IEEE International Conference on Robotics and Automation, 2007.
8. N.S. Pollard, Parallel algorithms for Synthesis of Whole-Hand Grasps, In Proceedings of IEEE Int. Conf. on Robotics and Automation, 1997.
9. Y. Li, J.L. Fu and N. Pollard, Data-Driven Grasp Synthesis Using Shape Matching and Task-Based Pruning, IEEE Transactions on Visualization and Computer Graphics, vol. 13:(4), pp. 732-747, 2007.
10. A. Saxena, J. Driemeyer, J. Kearns and A.Y. Ng, Robotic Grasping of Novel Objects using Vision, The International Journal of Robotics Research, vol. 27(2), pp. 157-173, 2008.
11. F. Kyota, T. Watabe, S. Saito and M. Nakajima, Detection and Evaluation of Grasping Positions for Autonomous Agents, In International Conference on Cyberworlds, pp. 453460, 2005.
12. J. Aleotti and S. Caselli, Robot Grasp Synthesis from Virtual Demonstration and Topology-Preserving Environment Reconstruction, In IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 2007.
13. L. Chen and N. D. Georganas, An efficient and robust algorithm for 3D mesh segmentation, Multimedia Tools Appl. 29(2): 109-125, 2006.
14. S. Ekvall and D. Kragic, Interactive grasp learning based on humain demonstration, IEEE/RSJ Int. Conf. on Robotics and Automation, New Orleans, USA, 2004.
15. M. Fischer, P. Van der Smagt and G. Hirzinger, Learning techniques in a dataglove based telemanipulation system for the DLR Hand, Proc. IEEE International Conference on Robotics and Automation, 1998.
16. M. Hueser, T. Baier and J. Zhang, Learning of demonstrated grasping skills by stereoscopic tracking of human hand configuration, in Proc. IEEE Int. Conf. Robot. Automat., 2006.
17. Y. H. Liu, Qualitative test and force optimization of 3-D frictional form closure grasps using linear programming, IEEE Transactions on Robotics and Automation, vol. 15, no. 1, 1999.
18. R. Pelossof, A. Miller, P. Allen and T. Jebara, An SVM learning appraoch to robotic grasping, IEEE Int. Conf. on Robotics and Automation, New Orleans, 2004, pp. 3512-3518.
19. X. Zhu and J. Wang, Synthesis of force-closure grasps on 3-D objects based on the Q distance, IEEE Trans. Robotics and Automation, vol. 19, no. 4, pp. 669-679, 2003.
20. E. Oztop and M. A. Arbib, Schema Design and Implementation of the Grasp-Related Mirror Neuron System, Biological Cybernetics 87: (2) 116-140, 2002.
21. V.D. Nguyen, Constructing Stable Grasps in 3D, Proc. of Int. Conf. on Robotics and Automation, pp. 234-239, 1987.
22. A. Bicchi, On the closure properties of robotic grasping, Int. J. Robot. Res., vol. 14, no. 4, pp. 319-334, 1995.
23. B. Mirtich and J. Canny, Easily Computable Optimum Grasps in 2-D and 3-D, Proc. IEEE Int. Conf. Robot. Automat., vol. 1, pp. 739-747, 1994.
24. D. Ding, Y.H. Liu, and S. Wang, Computing 3D optimal form-closure grasps, Proc. IEEE Int. Conf. Robot. Automat., 2000.
25. I. Biederman, Recognition-by-Components: A Theory of Human Image Understanding, Psychological Review, 1987, vol. 94, pp 115-147.
26. C.M. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, 1995.
27. S. Khoury and A. Sahbani, On Computing Robust N-Finger Force-Closure Grasps of 3D Objects, IEEE International Conference on Robotics and Automation, pp. 2480-2486, Japan, 2009.
28. Ch. Borst, M. Fischer and G. Hirzinger, Grasping the dice by dicing the grasp, IEEE Int. Conf. on Intelligent Robots and Systems, 2003.
29. N. Niparnan and A. Sudsang, Positive span of force and torque components of four-fingered three-dimensional force-closure grasps, IEEE Intl. Conf. on Robotics and Automation, 2007.
30. A.T. Miller, S. Knoop, P.K. Allen and H.I. Christensen, Automatic grasp planning using shape primitives, Proc. IEEE Intl. Conf. on Robotics and Automation, 2003.
31. J. Cortes, Motion planning algorithms for general closed-chain mechanisms, PhD thesis, 2003.