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Autonomous Robots

, Volume 41, Issue 2, pp 333–347 | Cite as

Learning autonomous behaviours for the body of a flexible surgical robot

  • Danilo Bruno
  • Sylvain Calinon
  • Darwin G. Caldwell
Article

Abstract

This paper presents a novel strategy to learn a positional controller for the body of a flexible surgical manipulator used for minimally invasive surgery. The manipulator is developed within the STIFF-FLOP European project and is targeted for a laparoscopic use in remote areas of the abdominal region that are not easily accessible by means of currently available rigid tools. While the surgeon controls the end-effector during the task, the flexible body of the manipulator needs to be displaced to enter inside constrained spaces by efficiently exploiting its flexibility, without touching vital organs and structures. The proposed algorithm exploits the instruments of machine learning within the programming by demonstrations paradigm to produce a statistical model of the natural movements of the surgeon during the task. The gathered information is then reused to determine a controller in the null space of the robot that does not interfere with the surgeon task and displaces the robot body within the available space in a fully automated manner.

Keywords

Learning from demonstrations Surgical robotics Online learning Nullspace control 

Notes

Acknowledgments

This work was partially supported by the STIFF-FLOP European project under contract FP7-ICT-287728.

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

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

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