Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-16T11:15:40.109Z Has data issue: false hasContentIssue false
  • English
  • Français

Modeling of contact pressure distribution and friction limit surfaces for soft fingers in robotic grasping

Published online by Cambridge University Press:  02 January 2014

Sadeq Hussein Bakhy
Sadeq Hussein Bakhy*
Affiliation:
Department of Machines and Equipment Engineering, University of Technology, Baghdad, Iraq
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

A new theory in contact pressure distribution and friction limit surfaces for modeling of hemicylindrical soft fingertips is introduced, to define the relationship between friction force and the moment with respect to the normal axis of contact. A general pressure-distribution function is proposed to capture material properties and contact geometry with various pressure profiles, and the coefficient of pressure distribution over the rectangular contact area is found between π and π/2. Combining the results of the contact mechanics model with the contact pressure distribution, the normalized friction limit surface can be derived for anthropomorphic soft fingers. The numerical friction limit surface of hemicylindrical soft-finger contact can be approximated by an ellipse, with the major and minor axes as the maximum friction force and the maximum moment with respect to the normal axis of contact, respectively. The results show that the friction limit surfaces are improved (13%–17%), if hemicylindrical fingertips are used rather than hemispherical fingertips at the same radius of fingertip, shape factor of the pressure profile, and applied load. Furthermore, the results of the contact mechanics model and the pressure distribution for soft fingers facilitate the construction of numerical friction limit surfaces, enabling to analyze and simulate the contact behaviors of grasping and manipulation in humanoid robots, prosthetic hands, and robotic hands.

Keywords

Humanoid robotsGraspingRobotic handsNovel applications of roboticsNonprehensile manipulation
Type
Articles
Information
Robotica , Volume 32 , Issue 7 , October 2014 , pp. 1005 - 1015
Copyright
Copyright © Cambridge University Press 2014 

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.Kao, I., Lynch, K. and Burdick, J. W., “Contact modeling and manipulation,” In: Springer Handbook of Robotics (Siciliano, B. and Khatib, O., eds.) (Springer, Berlin, 2008) pp. 647–669.CrossRefGoogle Scholar
2.Xydas, N. and Kao, I., “Modeling of contact mechanics and friction limit surface for soft fingers in robotics, with experimental results,” Int. J. Robot. Res. 18 (8), 941–950 (1999).CrossRefGoogle Scholar
3.Elango, N. and Marappan, R., “Development of contact model of a robot soft finger for power grasping and determination of its contact width,” Int. J. Recent Trends Eng. 1 (5), 5–9 (2009).Google Scholar
4.Bakhy, S. H., Hassan, S. S., Nacy, S. M., Dermitzakis, K. and Arieta, A. H., “Contact mechanics for soft robotic fingers: Modeling and experimentation,” Robotica 31 (4), 599–609 (2013).CrossRefGoogle Scholar
5.Goyal, S., Ruina, A. and Papadopoulos, J., “Planar sliding with dry friction: Part 1. Limit surface and moment function, and Part 2. Dynamics of motion,” Wear 143, 307–352 (1991).CrossRefGoogle Scholar
6.Howe, R. D. and Cutkosky, M. R., “Practical force-motion models for sliding manipulation,” Int. J. Robot. Res. 15 (6), 555–572 (1996).CrossRefGoogle Scholar
7.Xydas, N. and Kao, I., “Modeling of Contacts and Force/Moment for Anthropomorphic Soft Fingers,” Proceedings of the International Conference on Intelligent Robots and Systems (IROS), Victoria, Canada (1998) pp. 488–493.Google Scholar
8.Li, Y. and Kao, I., “A Review of Modeling of Soft-Contact Fingers and Stiffness Control for Dexterous Manipulation in Robotics,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seoul, South Korea (2001) pp. 3055–3060.Google Scholar
9.Howe, R. D., Kao, I. and Cutkosky, M. R., “Sliding of Robotic Fingers Under Combined Torsion and Shear Loading,” Proceedings of the International Conference on Robotics and Automation (ICRA), Philadelphia, USA (1988) pp. 103–105.Google Scholar
10.Shimoga, K. B. and Goldenberg, A. A., “Soft robotic fingertips – Parts I and II: A comparison of construction materials,” Int. J. Robot. Res. 15 (4), 320–334 (1996).CrossRefGoogle Scholar
11.Tsai, C.-H. Dylan, Kao, I., Higashimori, M. and Kaneko, M., “Modeling, sensing, and interpretation of viscoelastic contact interface,” Adv. Robot. 26 (11–12), 1393–1418 (2012).CrossRefGoogle Scholar
12.Hertz, H., “On the contact of elastic solids,” J. Reine Angew. Math. 92, 156–171 (1881).Google Scholar
13.Timoshenko, S. P. and Goodier, J. N., Theory of Elasticity, 3rd ed. (McGraw-Hill, Tokyo, 1970) pp. 414–420.Google Scholar
14.Hearn, E. J., Mechanics of Materials Part (2): Introduction to the Mechanics of Elastic and Plastic Deformation of Solids and Structural Materials, 3rd ed. (Antony Rowe, Eastbourne, UK, 2001) pp. 386–387.Google Scholar
15.Emil, W., Progress in Optics, Vol. 30 (North-Holland, New York, 1992).Google Scholar
16.Nicolson, E. J. and Fearing, R. S., “The Reliability of Curvature Estimates from Linear Elastic Tactile Sensors,” Proceedings of the IEEE International Conference on Robotics and Automation, Washington, DC, USA (1995), Vol. 1, pp. 1126–1133.Google Scholar
17.Kreyszig, E., Advanced Engineering Mathematics, 9th ed. (John Wiley, New York, 2006) pp. 192–193.Google Scholar
18.Kao, S.-F. Chen, Li, Y. and Wang, G., “Application of bio-engineering contact interface and MEMS in robotic and human augmented systems,” IEEE Robot. Autom. Mag. 10 (1), 47–53 (2003).Google Scholar
19.Kao, I., Wu, X. and Chen, S., “Dual relationship in dexterous sliding manipulation under force and position control,” Int. J. Robot. Autom. 14 (2), 68–77 (1999).Google Scholar