Transfer of learned dynamics between different surgical robots and operative configurations.

Journal: International journal of computer assisted radiology and surgery
PMID: 35384551

Abstract

PURPOSE: Using the da Vinci Research Kit (dVRK), we propose and experimentally demonstrate transfer learning (Xfer) of dynamics between different configurations and robots distributed around the world. This can extend recent research using neural networks to estimate the dynamics of the patient side manipulator (PSM) to provide accurate external end-effector force estimation, by adapting it to different robots and instruments, and in different configurations, with additional forces applied on the instruments as they pass through the trocar.

Authors

  • Nural Yilmaz
    Department of Mechanical Engineering, Marmara University, Istanbul, 34722, Turkey. nural.yilmaz@marun.edu.tr.
  • Jintan Zhang
    Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA.
  • Peter Kazanzides
  • Ugur Tumerdem
    Department of Mechanical Engineering, Marmara University, Istanbul, 34722, Turkey.

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