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Quasi-Static Analysis of Synergistically Underactuated Robotic Hands in Grasping and Manipulation Tasks

  • Edoardo FarnioliEmail author
  • Marco Gabiccini
  • Antonio Bicchi
Chapter
Part of the Springer Series on Touch and Haptic Systems book series (SSTHS)

Abstract

As described in Chaps.  2 5, neuroscientific studies showed that the control of the human hand is mainly realized in a synergistic way. Recently, taking inspiration from this observation, with the aim of facing the complications consequent to the high number of degrees of freedom, similar approaches have been used for the control of robotic hands. As Chap.  12 describes SynGrasp, a useful technical tool for grasp analysis of synergy-inspired hands, in this chapter recently developed analysis tools for studying robotic hands equipped with soft synergy underactuation (see Chap.  8) are exhaustively described under a theoretical point of view. After a review of the quasi-static model of the system, the Fundamental Grasp Matrix (FGM) and its canonical form (cFGM) are presented, from which it is possible to extract relevant information as, for example, the subspaces of the controllable internal forces, of the controllable object displacements and the grasp compliance. The definitions of some relevant types of manipulation tasks (e.g. the pure squeeze, realized maintaining the object configuration fixed but changing contact forces, or the kinematic grasp displacements, in which the grasped object can be moved without modifying contact forces) are provided in terms of nullity or non-nullity of the variables describing the system. The feasibility of such predefined tasks can be verified thanks to a decomposition method, based on the search of the row reduced echelon form (RREF) of suitable portions of the solution space. Moreover, a geometric interpretation of the FGM and the possibility to extend the above mentioned methods to the study of robotic hands with different types of underactuation are discussed. Finally, numerical results are presented for a power grasp example, the analysis of which is initially performed for the case of fully-actuated hand, and later verifying, after the introduction of a synergistic underactuation, which capacities of the system are lost, and which other are still present.

Keywords

Contact Force Joint Torque Manipulation Task Virtual Hand Robotic Hand 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was supported by the European Commission under the CP-IP grant no. 248587 “THE Hand Embodied”, within the FP7-2007-2013 program “Cognitive Systems and Robotics”, the ERC Advanced Grant no. 291166 “SoftHands: A Theory of Soft Synergies for a New Generation of Artificial Hands”, and by the grant no. 600918 “PaCMan” - Probabilistic and Compositional Representations of Objects for Robotic Manipulation - within the FP7-ICT-2011-9 program “Cognitive Systems”.

References

  1. 1.
    Jacobsen S, Wood J, Knutt D, Biggers K (1984) The Utah/MIT dextrous hand: work in progress. Int J Robot Res 3(4):21–50Google Scholar
  2. 2.
    Lovchik C, Diftler M (1999) The robonaut hand: a dexterous robot hand for space. In: Proceedings of 1999 IEEE International conference on robotics and automation, vol 2. pp 907–912Google Scholar
  3. 3.
    Shadow Robot Company Ltd. (2009) Shadow hand. http://shadowhand.com
  4. 4.
    Grebenstein M, Chalon M, Friedl W, Haddadin S, Wimbck T, Hirzinger G, Siegwart R (2012) The hand of the dlr hand ARM system: designed for interaction. Int J Robot Res 31(13):1531–1555Google Scholar
  5. 5.
    Fish J, Soechting JF (1992) Synergistic finger movements in a skilled motor task. Exp Brain Res 91(2):327–334Google Scholar
  6. 6.
    Angelaki DE, Soechting JF (1993) Non-uniform temporal scaling of hand and finger kinematics during typing. Exp Brain Res 92(2):319–329Google Scholar
  7. 7.
    Soechting JF, Flanders M (1997) Flexibility and repeatability of finger movements during typing: analysis of multiple degrees of freedoms. J Comput Neurosci 4(1):29–46Google Scholar
  8. 8.
    Santello M, Flanders M, Soechting J (1998) Postural hand synergies for tool use. J Neurosci 18:10105–10115Google Scholar
  9. 9.
    Latash, ML, Krishnamoorthy V, Scholz JP, Zatsiorsky VM (2005) Postural synergies and their development. Neural Plast 12:119–130, discussion 263–272Google Scholar
  10. 10.
    Thakur PH, Bastian AJ, Hsiao SS (2008) Multidigit movement synergies of the human hand in an unconstrained haptic exploration task. J Neurosci 28:1271–1281Google Scholar
  11. 11.
    Castellini C, van der Smagt P (2013) Evidence of muscle synergies during human grasping. Biol Cybern 107:233–245Google Scholar
  12. 12.
    Ciocarlie M, Goldfeder C, Allen P (2007) Dexterous grasping via eigengrasps: a low-dimensional approach to a high-complexity problem. In: Proceedings of the robotics: science and systems 2007 workshop-sensing and adapting to the real world. Electronically PublishedGoogle Scholar
  13. 13.
    Brown CY, Asada HH (2007) Inter-finger coordination and postural synergies in robot hands via mechanical implementation of principal components analysis. In: 2007 IEEE/RSJ international conference on intelligent robots and system, pp 2877–2882Google Scholar
  14. 14.
    Gabiccini M, Bicchi A, Prattichizzo D, Malvezzi M (2011) On the role of hand synergies in the optimal choice of grasping forces. Auton Robots [special issue on RSS2010] 31(2–3):235–252Google Scholar
  15. 15.
    Prattichizzo D, Malvezzi M, Bicchi A (2010) On motion and force controllability of grasping hands with postural synergies. In: Robotics: science and systems, vol VI. The MIT Press, Zaragoza, pp 49–56Google Scholar
  16. 16.
    Gabiccini M, Farnioli E, Bicchi A (2012) Grasp and manipulation analysis for synergistic underactuated hands under general loading conditions. In: International conference of robotics and automation—ICRA 2012, Saint Paul, MN, USA, pp 2836–2842, 14–18 May 2012Google Scholar
  17. 17.
    Gabiccini M, Farnioli E, Bicchi A (2013) Grasp analysis tools for synergistic underactuated robotic hands. Int J Robot Res 32:1553–1576Google Scholar
  18. 18.
    Farnioli E, Gabiccini M, Bonilla M, Bicchi A (2013) Grasp compliance regulation in synergistically controlled robotic hands with VSA. In: IEEE/RSJ international conference on intelligent robots and systems, IROS 2013, Tokyo, Japan, pp 3015–3022. 3–7 Nov 2013Google Scholar
  19. 19.
    Meyer CD (2000) Matrix analysis and applied linear algebra. Society for Industrial and Applied Mathematics, PhiladelphiaGoogle Scholar
  20. 20.
    Bicchi A, Melchiorri C, Balluchi D (1995) On the mobility and manipulability of general multiple limb robotic systems. IEEE Trans Robot Autom 11:215–228Google Scholar
  21. 21.
    Bonilla M, Farnioli E, Pallottino L, Bicchi A (2015) Sample-based motion planning for soft robot manipulators under task constraints. In: Accepted to international conference of robotics and automation—ICRA 2015Google Scholar
  22. 22.
    Birglen L, Laliberté T, Gosselin C (2008) Underactuated robotic hands. Springer tracts in advanced robotics, vol 40. Springer, BerlinGoogle Scholar
  23. 23.
    Catalano MG, Grioli G, Serio A, Farnioli E, Piazza C, Bicchi A (2012) Adaptive synergies for a humanoid robot hand. In: IEEE-RAS international conference on humanoid robots, Osaka, JapanGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Edoardo Farnioli
    • 1
    • 2
    Email author
  • Marco Gabiccini
    • 1
    • 2
    • 3
  • Antonio Bicchi
    • 1
    • 2
  1. 1.Research Center “E. Piaggio”Università di PisaPisaItaly
  2. 2.Department of Advanced RoboticsIstituto Italiano di TecnologiaGenoaItaly
  3. 3.Department of Civil and Industrial EngineeringUniversità di PisaPisaItaly

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