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Optimal Exploitation of Soft-Robot Dynamics

  • Sami Haddadin
Conference paper

Abstract

Inspired by the elasticity contained in human muscles, elastic soft robots are designed with the aim of imitating motions as observed in humans or animals. Especially reaching peak velocities using stored energy in the springs is a task of significant interest. In this chapter, general results on maximizing a softrobot’s end-point velocity by using elastic joint energy are presented and discussed.

Keywords

Intelligent Robot Variable Stiffness Angular Deflection Soft Robot Elastic Joint 
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.

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References

  1. [1]
    Albu-Schäffer A, Eiberger O, Grebenstein M, Haddadin S, Ott C, Wimböck T, Wolf S, Hirzinger G (2008) Soft robotics: From torque feedback controlled lightweight robots to intrinsically compliant systems. IEEE Robotics and Automation Mag: Special Issue on Adaptable Compliance/Variable Stiffness for Robotic Applications 15(3): 20–30CrossRefGoogle Scholar
  2. [2]
    Bäuml B, Schmidt F, Wimböck T (2011) Catching flying balls and preparing coffee: Humanoid rollin’ justin performs dynamic and sensitive tasks. International Conference on Robotics and Automation pp. 3443–3444Google Scholar
  3. [3]
    Bicchi A, Tonietti G (2004) Fast and soft arm tactics: Dealing with the safety-performance trade-off in robot arms design and control. IEEE Robotics and Automation Magazine 11:22–33Google Scholar
  4. [4]
    Braun D, Howard M, Vijayakumar S (2011) Exploiting variable stiffness in explosive movement tasks. Proceedings of Robotics: Science and SystemsGoogle Scholar
  5. [5]
    Eiberger O, Haddadin S, Weis M, Albu-Schäffer A, Hirzinger G (2010) On joint design with intrinsic variable compliance: derivation of the DLR QA-Joint. International Con-ference on Robotics and Automation pp. 1687–1694Google Scholar
  6. [6]
    Garabini M, Passaglia A, Belo F, Salaris P, Bicchi A (2011) Optimality principles in var-iable stiffness control: the vsa hammer. International Conference on Intelligent Robots and Systems pp. 3770–3775Google Scholar
  7. [7]
    Grebenstein M, Albu-Schäffer A et al (2011) The DLR hand arm system pp. 3175–3182.Google Scholar
  8. [8]
    Haddadin S, Krieger K, Mansfeld N, Albu-Schäffer A (2012) On impact decoupling properties of elastic robots and time optimal velocity maximization on joint level. Inter-national Conference on Intelligent Robots and Systems pp. 5089–5096Google Scholar
  9. [9]
    Haddadin S, Albu-Schäffer A, Eiberger O, Hirzinger G (2010) New insights concerning intrinsic joint elasticity for safety. International Conference on Intelligent Robots and Systems pp. 2181–2187Google Scholar
  10. [10]
    Haddadin S, Laue T, Frese U, Wolf S, Albu-Schäffer A, Hirzinger G (2009) Kick it with elasticity: Requirements for 2050. Robotics and Autonomous Systems 57:761–775Google Scholar
  11. [11]
    Haddadin S, Weis M, Wolf S, Albu-Schäffer A (2011) Optimal control for maximizing link velocity of robotic variable stiffness joints. Proceedings of the International Federa-tion of Automatic Control pp. 3175–3182Google Scholar
  12. [12]
    Liberzon D (2011) Calculus of Variations and Optimal Control Theory: A Concise Intro-duction, Princeton University PressGoogle Scholar
  13. [13]
    Mettin U, Shiriaev A (2011) Ball-pitching challenge with an underactuated two-link ro-bot arm. International Federation of Automatic Control pp. 1–6Google Scholar
  14. [14]
    Özparpucu M, Haddadin S (2013) Optimal control for maximizing link velocity of a vis-co-elastic joint. Int Conf on Intelligent Robots and Systems pp. 3035–3042Google Scholar
  15. [15]
    Paluska D, Herr H (2006) The effect of series elasticity on actuator power and work out-put: Implications for robotic and prosthetic joint design. Robotics and Autonomous Sys-tems 54:667–673Google Scholar
  16. [16]
    Ham R, Sugar T, Vanderborgth B, Hollander K, Lefeber D (2009) Compliant actuator designs: Review of actuators with passive adjustable compliance/controllable stiffness for robotic applications. IEEE Robotics and Automation Mag 16(3):81–94Google Scholar
  17. [17]
    Vanderborght B, Verrelst B, Ham Rv, Damme Mv, Lefeber D, Duran B, Beyl P (2006) Exploiting natural dynamics to reduce energy consumption by controlling the compliance of soft actuators. International Journal of Robotics Research 25(4):343–358CrossRefGoogle Scholar
  18. [18]
    Yamaguchi J, Inoue S, Nishino D, Takanishi A (1998) Development of a bipedal human-oid robot having antagonistic driven joints and three DOF trunk. Int. Conf. on Intelligent Robots and Systems pp. 96–101Google Scholar
  19. [19]
    Yamaguchi J, Nishino D, Takanishi A (1998) Realization of dynamic biped walking var-ying joint stiffness using antagonistic driven joints. Int Conf on Robotics and Automation pp. 2022–2029Google Scholar
  20. [20]
    Özparpucu M, Haddadin S (2014) Optimal Control of Elastic Joints with Variable Damp-ing, European Control Conference pp. 2256–2533Google Scholar
  21. [21]
    Haddadin S, Huber F, Albu-Schäffer A (2012) Optimal control for exploiting the natural dynamics of variable stiffness robots. Int Conf on Robotics and Automation pp. 3347–3354Google Scholar
  22. [22]
    Haddadin S, Can Özparpucu M, Albu-Schäffer A (2012) Optimal control for maximizing potential energy in a variable stiffness joint. Conference on Decision and Control pp. 1199–1206Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Sami Haddadin
    • 1
  1. 1.Leibniz Universität HannoverHannoverGermany

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