Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-22T09:06:05.525Z Has data issue: false hasContentIssue false
  • English
  • Français

Stable pinching by controlling finger relative orientation of robotic fingers with rolling soft tips

Published online by Cambridge University Press:  14 August 2017

Efi Psomopoulou Open the ORCID record for Efi Psomopoulou [Opens in a new window] ,
Daiki Karashima ,
Zoe Doulgeri  and
Kenji Tahara
Efi Psomopoulou
Affiliation:
School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece. E-mail: [email protected]
Daiki Karashima
Affiliation:
Faculty of Engineering, Kyushu University, Fukuoka 819-0395, Japan. E-mails: [email protected], [email protected]
Zoe Doulgeri*
Affiliation:
School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece. E-mail: [email protected]
Kenji Tahara
Affiliation:
Faculty of Engineering, Kyushu University, Fukuoka 819-0395, Japan. E-mails: [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

There is a large gap between reality and grasp models that are currently available because of the static analysis that characterizes these approaches. This work attempts to fill this need by proposing a control law that, starting from an initial contact state which does not necessarily correspond to an equilibrium, achieves dynamically a stable grasp and a relative finger orientation in the case of pinching an object with arbitrary shape via rolling soft fingertips. Controlling relative finger orientation may improve grasping force manipulability and allow the appropriate shaping of the composite object consisted of the distal links and the object, for facilitating subsequent tasks. The proposed controller utilizes only finger proprioceptive measurements and is not based on the system model. Simulation and experimental results demonstrate the performance of the proposed controller with objects of different shapes.

Keywords

Stable pinchingRelative finger orientationSoft rolling contactFeedback control
Type
Articles
Information
Robotica , Volume 36 , Issue 2 , February 2018 , pp. 204 - 224
Copyright
Copyright © Cambridge University Press 2017 

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. Mason, M. T. and Salisbury, J. K., Robot Hands and the Mechanics of Manipulation (MIT Press, Cambridge, MA, 1985).Google Scholar
2. Kawasaki, H., Komatsu, T. and Uchiyama, K., “Dexterous anthropomorphic robot hand with distributed tactile sensor: Gifu hand II,” IEEE/ASME Trans. Mechatronics 7 (3), 296–303 (2002).Google Scholar
3. Hoshino, K. and Kawabuchi, I., “Pinching at fingertips for humanoid robot hand,” J. Robot. Mechatronics 17 (6), 655–663 (2005).Google Scholar
4. Liu, H., Wu, K., Meusel, P., Seitz, N., Hirzinger, G., Jin, M., Liu, Y., Fan, S., Lan, T. and Chen, Z., “Multisensory Five-Finger Dexterous Hand: The DLR/HIT Hand II,” IEEE/RSJ International Conference on Intelligent Robots and Systems (Nice, France, Sep. 2008) pp. 3692–3697.Google Scholar
5. SHADOW, “Shadow dexterous hand,” built by the Shadow Robot Company based in London, UK. http://www.shadowrobot.com/products/dexterous-hand/ Google Scholar
6. Zribi, M., Chen, J. and Mahmoud, M., “Coordination and control of multi-fingered robot hands with rolling and sliding contacts,” J. Intell. Robot. Syst. 24 (2), 125–149 (1999).Google Scholar
7. Arimoto, S., Control Theory of Multi-fingered Hands: A Modelling and Analytical-mechanics Approach for Dexterity and Intelligence (Springer-Verlag, London Limited, London, 2008).Google Scholar
8. Bicchi, A., “Hands for dexterous manipulation and robust grasping: A difficult road toward simplicity,” IEEE Trans. Robot. Autom. 16 (6), 652–662 (2000).Google Scholar
9. Wimbock, T., Ott, C., Albu-Schaffer, A. and Hirzinger, G., “Comparison of object-level grasp controllers for dynamic dexterous manipulation,” Int. J. Robot. Res. 31 (1), 3–23 (2011).Google Scholar
10. Bohg, J., Morales, A., Asfour, T. and Kragic, D., “Data-driven grasp Synthesis–a survey,” IEEE Trans. Robot. 30 (2), 289–309 (2013).Google Scholar
11. Farshchi, S., “Let's Bring Rosie Home: 5 Challenges We Need to Solve for Home Robots,” In: IEEE Spectrum's Automaton (Guizzo, E., ed.) (2016). http://spectrum.ieee.org/automaton/robotics/home-robots/lets-bring-rosie-home-5-challenges-we-need-to-solve-for-home-robots Google Scholar
12. Murray, R. and Sastry, S., A Mathematical Introduction to Robotic Manipulation (CRC Press INC, Boca Raton, Florida, USA, 1994).Google Scholar
13. Bicchi, A. and Kumar, V., “Robotic Grasping and Contact: A Review,” IEEE International Conference on Robotics and Automation (San Fransisco, CA, USA, 2000) pp. 348–353.Google Scholar
14. Prattichizzo, D. and Trinkle, J. C., “Grasping,” In: Springer Handbook of Robotics (Prof. Siciliano, B. and Prof. Khatib, O. eds.) (Springer, Berlin, Heidelberg, 2008) pp. 671–700.CrossRefGoogle Scholar
15. Prattichizzo, D., Malvezzi, M., Gabiccini, M. and Bicchi, A., “On the manipulability ellipsoids of underactuated robotic hands with compliance,” In: Robot. Auton. Syst. (Prof. Siciliano, B. and Prof. Khatib, O., eds.) 60 (3), 337–346 (2012).Google Scholar
16. Roa, M. A. and Suarez, R., “Computation of independent contact regions for grasping 3-D objects,” IEEE Trans. Robot. 25 (4), 839–850 (2009).Google Scholar
17. Krug, R., Dimitrov, D., Charusta, K. and Iliev, B., “On the Efficient Computation of Independent Contact Regions for Force Closure Grasps,” IEEE/RSJ International Conference on Intelligent Robots and Systems (Taipei, Taiwan, Oct. 2010) pp. 586–591.Google Scholar
18. Rosales, C., Suarez, R., Gabiccini, M. and Bicchi, A., “On the Synthesis of Feasible and Prehensile Robotic Grasps,” Proceedings of the 2012 IEEE International Conference on Robotics and Automation (Saint Paul, MN, USA, May 2012) pp. 550–556.Google Scholar
19. Rodriguez, A., Mason, M. T. and Ferry, S., “From Caging to Grasping,” In: Robotics: Science and Systems Conference (RSS) (Los Angeles, Pittsburgh, PA, USA, 2011) pp. 1–8.Google Scholar
20. Seo, J., Kim, S. and Kumar, V., “Planar, Bimanual, Whole-Arm Grasping,” IEEE International Conference on Robotics and Automation (Saint Paul, MN, USA, May 2012) pp. 3271–3277.CrossRefGoogle Scholar
21. Zhang, L. and Trinkle, J. C., “The Application of Particle Filtering to Grasping Acquisition with Visual Occlusion and Tactile Sensing,” IEEE International Conference on Robotics and Automation (Saint Paul, MN, USA, May 2012) pp. 3805–3812.Google Scholar
22. Miller, A. T. and Allen, P. K., “GraspIt!” IEEE Robot. Autom. Mag. 11 (4), 110–122 (2004).Google Scholar
23. Miller, A. T., Knoop, S., Christensen, H. I. and Allen, P. K., “Automatic Grasp Planning using Shape Primitives,” IEEE International Conference on Robotics and Automation (Taipei, Taiwan, Sep. 2003) pp. 1824–1829.Google Scholar
24. Pelossof, R., Miller, A., Allen, P. and Jebara, T., “An SVM Learning Approach to Robotic Grasping,” IEEE International Conference on Robotics and Automation (New Orleans, LA, USA, Apr. 2004) pp. 3512–3518.Google Scholar
25. Goldfeder, C., Allen, P. K., Lackner, C. and Pelossof, R., “Grasp Planning Via Decomposition Trees,” IEEE International Conference on Robotics and Automation (Rome, Italy, Apr. 2007) pp. 4679–4684.CrossRefGoogle Scholar
26. Borst, C., Fischer, M. and Hirzinger, G., “Grasping the Dice by Dicing the Grasp,” IEEE/RSJ International Conference on Intelligent Robots and Systems (Las Vegas, NV, USA, Oct. 2003) pp. 3692–3697.Google Scholar
27. Ciocarlie, M. T. and Allen, P. K., “Hand posture subspaces for dexterous robotic grasping,” Int. J. Robot. Res. 28 (7), 851–867 (2009).CrossRefGoogle Scholar
28. Balasubramanian, R., Xu, L., Brook, P. D., Smith, J. R. and Matsuoka, Y., “Physical human interactive guidance: Identifying grasping principles from human-planned grasps,” IEEE Trans. Robot. 28 (4), 899–910 (2012).Google Scholar
29. Weisz, J. and Allen, P. K., “Pose Error Robust Grasping from Contact Wrench Space Metrics,” IEEE International Conference on Robotics and Automation (Saint Paul, MN, USA, May 2012) pp. 557–562.CrossRefGoogle Scholar
30. Kappler, D., Bohg, J. and Schaal, S., “Leveraging Big Data for Grasp Planning,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), IEEE (Seattle, WA, USA, May 2015) pp. 4304–4311.Google Scholar
31. Johns, E., Leutenegger, S. and Davison, A. J., “Deep Learning a Grasp Function for Grasping Under Gripper Pose Uncertainty,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, Daejeon, South Korea (Oct. 2016) pp. 4461–4468.CrossRefGoogle Scholar
32. Arimoto, S., Nguyen, P. T. A., Han, H.-Y. and Doulgeri, Z., “Dynamics and control of a set of dual fingers with soft tips,” Robotica 18 (1), 71–80 (2000).Google Scholar
33. Doulgeri, Z., Fasoulas, J. and Arimoto, S., “Feedback control for object manipulation by a pair of soft tip fingers,” Robotica 20 (1), 1–11 (2002).Google Scholar
34. Song, S. K., Park, J. B. and Choi, Y. H., “Dual-fingered stable grasping control for an optimal force angle,” IEEE Trans. Robot. 28 (1), 256–262 (2012).Google Scholar
35. Ozawa, R., Arimoto, S. and Nakamura, S., “Control of an object with parallel surfaces by a pair of finger robots without object sensing,” IEEE Trans. Robot. 21 (5), 965–976 (2005).Google Scholar
36. Arimoto, S., “A differential-geometric approach for 2D and 3D object grasping and manipulation,” Annu. Rev. Control 31 (2), 189–209 (2007).Google Scholar
37. Arimoto, S., Tahara, K., Yamaguchi, M., Nguyen, P. and Han, M.-Y., “Principles of superposition for controlling pinch motions by means of robot fingers with soft tips,” Robotica 19 (01), 21–28 (2001).Google Scholar
38. Arimoto, S., Tahara, K., Bae, J.-H. and Yoshida, M., “A stability theory of a manifold: Concurrent realization of grasp and orientation control of an object by a pair of robot fingers,” Robotica 21 (02), 163–178 (2003).Google Scholar
39. Yoshida, M., Arimoto, S. and Tahara, K., “Pinching 2D Object with Arbitrary Shape by Two Robot Fingers Under Rolling Constraints,” IEEE/RSJ International Conference on Intelligent Robots and Systems (St Louis, MO, USA, 2009) pp. 1805–1810.Google Scholar
40. Kawamura, A., Tahara, K., Kurazume, R. and Hasegawa, T., “Dynamic grasping of an arbitrary polyhedral object,” Robotica 31 (04), 511–523 (2013).Google Scholar
41. Grammatikopoulou, M., Psomopoulou, E., Droukas, L. and Doulgeri, Z., “A Controller for Stable Grasping and Desired Finger Shaping without Contact Sensing,” IEEE International Conference on Robotics and Automation (Hong Kong, China, May 2014) pp. 3662–3668.Google Scholar
42. Shimoga, K. and Goldenberg, A., “Soft robotic fingertips part II: Modeling and impedance regulation,” Int. J. Robot. Res. 15 (4), 335–350 (1996).Google Scholar
43. Chiacchio, P., Chiaverini, S., Sciavicco, L. and Siciliano, B., “Global task space manipulability ellipsoids for multiple-arm systems,” IEEE Trans. Robot. Autom. 7 (5), 678–685 (1991).CrossRefGoogle Scholar
44. Caccavale, F. and Uchiyama, M., “Cooperative Manipulators,” In: Springer Handbook of Robotics (Prof. Siciliano, B. and Prof. Khatib, O., eds.) (Springer, Berlin, Heidelberg, 2008) pp. 701–718.Google Scholar
45. Yoshikawa, T., Foundations of Robotics (MIT Press, Cambridge, MA, USA, 1990).Google Scholar
46. Tahara, K., Maruta, K., Kawamura, A. and Yamamoto, M., “Externally Sensorless Dynamic Regrasping and Manipulation by a Triple-Fingered Robotic Hand with Torsional Fingertip Joints,” IEEE International Conference on Robotics and Automation (Saint Paul, MN, USA, 2012) pp. 3252–3257.Google Scholar

Psomopoulou supplementary material

Psomopoulou supplementary material 1

Download Psomopoulou supplementary material(Video)
Video 14.8 MB