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BY-NC-ND 4.0 license Open Access Published by De Gruyter September 22, 2018

Assessment of Natural User Interactions for Robot-Assisted Interventions

  • Johann Berger EMAIL logo , Michael Unger , Lisa Landgraf , Richard Bieck , Thomas Neumuth and Andreas Melzer

Abstract

Robotic assistance in clinical interventions provides high precision and performance. However, the acceptance of such systems is still very low. The idea of collaborative robotics promises practical solutions for this problem. To further promote these ideas in the medical domain, novel concepts for user interactions are needed. This work presents a preliminary study on the recognition accuracy of touch gesture interaction with a KUKA LBR iiwa robotic arm. A recognition application utilising a set of 4 different touch gestures was implemented and evaluated by eight participants. The overall recognition accuracy of the system is 89.8%.

Published Online: 2018-09-22
Published in Print: 2018-09-01

© 2018 the author(s), published by Walter de Gruyter Berlin/Boston

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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