Autonomous Robots

, Volume 43, Issue 4, pp 927–946 | Cite as

A dynamical system approach to task-adaptation in physical human–robot interaction

  • Mahdi KhoramshahiEmail author
  • Aude Billard


The goal of this work is to enable robots to intelligently and compliantly adapt their motions to the intention of a human during physical Human–Robot Interaction in a multi-task setting. We employ a class of parameterized dynamical systems that allows for smooth and adaptive transitions between encoded tasks. To comply with human intention, we propose a mechanism that adapts generated motions (i.e., the desired velocity) to those intended by the human user (i.e., the real velocity) thereby switching to the most similar task. We provide a rigorous analytical evaluation of our method in terms of stability, convergence, and optimality yielding an interaction behavior which is safe and intuitive for the human. We investigate our method through experimental evaluations ranging in different setups: a 3-DoF haptic device, a 7-DoF manipulator and a mobile platform.


Physical human–robot interaction Adaptive behavior Compliant control Dynamical systems Predictive models 



We thank support from the European Communitys Horizon 2020 Research and Innovation programme ICT-23-2014, grant agreement 644727-CogIMon and 643950-SecondHands. Thanks to José R. Medina, Klas Kronander, and Guillaume deChambrier for their help with the controller implementations on Kuka LWR 4+ and Clearpath ridgeback.

Supplementary material

Supplementary material 1 (mp4 14313 KB)

Supplementary material 2 (mp4 18183 KB)


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Learning Algorithms and Systems LaboratorySwiss Federal Institute of TechnologyLausanneSwitzerland

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