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Reflective-AR Display: An Interaction Methodology for Virtual-to-Real Alignment in Medical Robotics

  • Javad Fotouhi
  • , Mathias Unberath
  • , Nassir Navab
  • , Tianyu Song
  • , Arian Mehrfard
  • , Giacomo Taylor
  • , Qiaochu Wang
  • , Fengfan Xian
  • , Alejandro Martin-Gomez
  • , Bernhard Fuerst
  • , Mehran Armand
  • Johns Hopkins University
  • Johns Hopkins University
  • Verb Surgical Inc.
  • Technical University of Munich

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

Robot-assisted minimally invasive surgery has shown to improve patient outcomes, as well as reduce complications and recovery time for several clinical applications. While increasingly configurable robotic arms can maximize reach and avoid collisions in cluttered environments, positioning them appropriately during surgery is complicated because safety regulations prevent automatic driving. We propose a head-mounted display (HMD) based augmented reality (AR) system designed to guide optimal surgical arm set up. The staff equipped with HMD aligns the robot with its planned virtual counterpart. In this user-centric setting, the main challenge is the perspective ambiguities hindering such collaborative robotic solution. To overcome this challenge, we introduce a novel registration concept for intuitive alignment of AR content to its physical counterpart by providing a multi-view AR experience via reflective-AR displays that simultaneously show the augmentations from multiple viewpoints. Using this system, users can visualize different perspectives while actively adjusting the pose to determine the registration transformation that most closely superimposes the virtual onto the real. The experimental results demonstrate improvement in the interactive alignment of a virtual and real robot when using a reflective-AR display. We also present measurements from configuring a robotic manipulator in a simulated trocar placement surgery using the AR guidance methodology.

Original languageEnglish
Article number8988155
Pages (from-to)2722-2729
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume5
Issue number2
DOIs
StatePublished - Apr 2020

Keywords

  • Surgical robotics: laparoscopy
  • augmented reality
  • computer vision for medical robotics

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