Hostname: page-component-8448b6f56d-xtgtn Total loading time: 0 Render date: 2024-04-18T06:58:50.940Z Has data issue: false hasContentIssue false
  • English
  • Français

Evaluation of 3D grasps with physical interpretations using object wrench space

Published online by Cambridge University Press:  11 July 2011

Hyunhwan Jeong  and
Joono Cheong
Hyunhwan Jeong
Affiliation:
Department of Control and Instrumentation Engineering, Korea University, Chungnam, South Korea
Joono Cheong*
Affiliation:
Department of Control and Instrumentation Engineering, Korea University, Chungnam, South Korea
*
*Corresponding author. E-mail: jncheong@korea.ac.kr
Get access Rights & Permissions [Opens in a new window]

Summary

In this paper we propose an intuitive and practical grasp quality measure for grasping 3D objects with a multi-fingered robot hand. The proposed measure takes into account the object geometries through the concept of object wrench space. Physically, the positive measure value has a meaning of the minimum single disturbance that grasp cannot resist, while the negative measure value implies the minimum necessary helping force that restores a non-force-closure grasp into a force-closure one. We show that the measure value is invariant between similar grasps and also between different torque origins. We verify the validity of the proposed measure via simulations by using computer models of a three-fingered robot hand and polygonal objects.

Keywords

Grasp measureRobot handForce-closureObject wrench space
Type
Articles
Information
Robotica , Volume 30 , Issue 3 , May 2012 , pp. 405 - 417
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Pollard, N. S., “Closure and quality equivalence for efficient synthesis of grasps from examples,” Int. J. Robot. Res. 23, 595–613 (2004).Google Scholar
2.Hershkovitz, M. and Teboulle, M., “Sensitivity analysis for a class of robotic grasping quality functionals,” Robotica 16, 227–235 (1998).CrossRefGoogle Scholar
3.Borst, C., Fischer, M. and Hirzinger, G., “Grasp planning: how to choose a suitable task wrench space,” Proc. IEEE Int. Conf. Robot. Autom. 1, 319–325 (2004).Google Scholar
4.Strandberg, M. and Wahlberg, B., “A method for grasp evaluation based on disturbance force rejection,” IEEE Trans. Robot. 22 (3), 461–469 (2006).Google Scholar
5.Nguyen, V.-D., “The Synthesis of Stable Force-Closure Grasps,” Technical Report 905, Massachusetts Institute of Technology, Cambridge, MA (1986).Google Scholar
6.Mishra, B., Schwartz, J. T. and Sharir, M., “On the existence and synthesis of multifinger positive grasp,” Algorithmica 2 (4), 541–558 (1987).Google Scholar
7.Ponce, J. and Faverjon, V., “On computing three-finger force-closure grasps of polygonal objects,” IEEE Trans. Robot. Autom. 11 (6), 868–881 (1995).Google Scholar
8.Kirkpatrick, D., Mishra, B. and Yap, C.-K., “Quantitative Steinitz's Theorems with Applications to Multifingered Grasping,” Proceedings of the ACM Symposium on Theory of Computing (1990) pp. 341–351.Google Scholar
9.Ferrarari, C. and Canny, J. F., “Planning optimal grasps,” Proc. IEEE Int. Conf. Robot. Autom. 3, 2290–2295 (1992).Google Scholar
10.Murray, R. M., Li, Z. and Sastry, S. S., A Mathematical Introduction to Robotic Manipulation. (CRC, Boca Raton, FL, 1993).Google Scholar
11.Liu, Y. H., “Qualitative test and force optimization of 3D frictional form-closure grasps using linear programming,” IEEE Trans. Robot. Autom. 15 (1), 163–173 (1999).Google Scholar
12.Li, Z. and Sastry, S. S., “Task-oriented optimal grasping by multifingered robot hands,” IEEE J. Robot. Autom. 4 (1), 32–44 (1988).CrossRefGoogle Scholar
13.Haschke, R., Steil, J., Steuwer, I. and Ritter, H., “Task-oriented Quality Measures for Dextrous Grasping,” Proceedings of the IEEE International Symposium on Computational Intelligence in Robotics and Automation (2005), pp. 689–694.Google Scholar
14.Cornelia, J. and Suarez, R., “Efficient determination of four-point form-closure optimal constraints of polygonal objects,” IEEE Trans. Autom. Sci. Eng. 6 (1), 121–130 (2009).Google Scholar
15.Yokokohji, Y., San Martin, J. and Fujiwara, M., “Dynamic manipulability of multifingered grasping,” IEEE Trans. Robot. 25 (4), 947–954 (2009).CrossRefGoogle Scholar
16.Salimi, S. and Bone, G. M., “Kinematic enveloping grasp planning method for robotic dexterous hands and three-dimensional objects,” Robotica 26, 331–344 (2008).Google Scholar
17.Arimoto, S., Ozawa, R. and Yoshida, M., “Two-Dimensional Stable blind Grasping under the Gravity Effect,” Proceedings of IEEE International Conference on Robotics and Automation (2005) pp. 1196–1202.Google Scholar
18.Nishimura, K. and Ohnishi, K., “Gravity Estimation and Compensation of Grasped Object for Bilateral Teleoperation,” IEEE International Workshop on Advanced Motion Control (2006) pp. 72–77.Google Scholar
19.Prattichizzo, D., Aslisbury, J. and Bicchi, A., “Contact and Grasp Robustness Measures: Analysis and Experiments,” Proceedings of Symposium on Experimental Robotics (1995) pp. 1–6.Google Scholar
20.Roa, M. A. and Suarez, R., “Computation of independent contact regions for grasping 3D objects,” IEEE Trans. Robot. Autom. 25 (4), 839–850 (2009).Google Scholar
21.Platt, R., Fagg, A. and Grupen, R., “Null-space grasp control: Theory and experiments,” IEEE Trans. Robot. 26, 282–295 (2010).Google Scholar
22.Zhu, X. and Wang, J., “Synthesis of force-closure grasps on 3D objects based on the q distance,” IEEE Trans. Robot. Autom. 19 (4), 669–679 (2003).Google Scholar
23.Jeong, H., Park, J., Cheong, J. and Park, F. C., “Grasp planning for three-fingerd robot hands using taxonomy-based preformed grasp and object primitives,” J. Korea Robot. Soc. 3, 123–130 (2008).Google Scholar