Image-Based Trajectory Tracking Control of 4-DoF Laparoscopic Instruments Using a Rotation Distinguishing Marker

Zerui Wang, Sing Chun Lee, Fangxun Zhong, David Navarro-Alarcon, Yun Hui Liu, Anton Deguet, Peter Kazanzides, Russell H. Taylor

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)


In this letter, we propose a new method to fully control complete 4-image-DoF manipulation of laparoscopic instruments [with remote center of motion (RCM) mechanism] based on the geometric features of a designed marker in a 2-D image. Our marker encodes the configuration of the instruments by computing geometric features among the projected image points from segmented areas in hue-saturation-value (HSV) space. We can then construct an image geometric feature vector to locally characterize the configuration of a laparoscopic instrument. Furthermore, we design an image-based kinematic controller to asymptotically track a planned trajectory using the constructed feature vector as the feedback. We evaluate our integration of rotation distinguishing marker and kinematic controller by several experiments in terms of illumination-invariance, rotation angle accuracy, and controller performance.

Original languageEnglish
Article number7867766
Pages (from-to)1586-1592
Number of pages7
JournalIEEE Robotics and Automation Letters
Issue number3
Publication statusPublished - Jul 2017
Externally publishedYes


  • Surgical robotics
  • Visual servoing

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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