International Conference on Intelligent Robotics and Applications

ICIRA 2015: Intelligent Robotics and Applications pp 185-195

Learning the Stiffness of a Continuous Soft Manipulator from Multiple Demonstrations

  • Danilo Bruno
  • Sylvain Calinon
  • Milad S. Malekzadeh
  • Darwin G. Caldwell
Conference paper

DOI: 10.1007/978-3-319-22873-0_17

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9246)
Cite this paper as:
Bruno D., Calinon S., Malekzadeh M.S., Caldwell D.G. (2015) Learning the Stiffness of a Continuous Soft Manipulator from Multiple Demonstrations. In: Liu H., Kubota N., Zhu X., Dillmann R., Zhou D. (eds) Intelligent Robotics and Applications. ICIRA 2015. Lecture Notes in Computer Science, vol 9246. Springer, Cham

Abstract

Continuous soft robots are becoming more and more widespread in applications, due to their increased safety and flexibility in critical applications. The possibility of having soft robots that are able to change their stiffness in selected parts can help in situations where higher forces need to be applied. This paper describes a theoretical framework for learning the desired stiffness characteristics of the robot from multiple demonstrations. The framework is based on a statistical mathematical model for encoding the motion of a continuous manipulator, coupled with an optimal control strategy for learning the best impedance parameters of the manipulator.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Danilo Bruno
    • 1
  • Sylvain Calinon
    • 1
    • 2
  • Milad S. Malekzadeh
    • 1
  • Darwin G. Caldwell
    • 1
  1. 1.Department of Advanced RoboticsIstituto Italiano di Tecnologia (IIT)GenovaItaly
  2. 2.Idiap Research InstituteMartignySwitzerland

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