Handheld micromanipulation with vision-based virtual fixtures

Brian C. Becker, Robert A. MacLachlan, Gregory D. Hager, Cameron N. Riviere

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Precise movement during micromanipulation becomes difficult in submillimeter workspaces, largely due to the destabilizing influence of tremor. Robotic aid combined with filtering techniques that suppress tremor frequency bands increases performance; however, if knowledge of the operator's goals is available, virtual fixtures have been shown to greatly improve micromanipulator precision. In this paper, we derive a control law for position-based virtual fixtures within the framework of an active handheld micromanipulator, where the fixtures are generated in real-time from microscope video. Additionally, we develop motion scaling behavior centered on virtual fixtures as a simple and direct extension to our formulation. We demonstrate that hard and soft (motion-scaled) virtual fixtures outperform state-of-the-art tremor cancellation performance on a set of artificial but medically relevant tasks: holding, move-and-hold, curve tracing, and volume restriction.

Original languageEnglish (US)
Title of host publication2011 IEEE International Conference on Robotics and Automation, ICRA 2011
Number of pages6
StatePublished - Dec 1 2011
Event2011 IEEE International Conference on Robotics and Automation, ICRA 2011 - Shanghai, China
Duration: May 9 2011May 13 2011

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729


Other2011 IEEE International Conference on Robotics and Automation, ICRA 2011

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Handheld micromanipulation with vision-based virtual fixtures'. Together they form a unique fingerprint.

Cite this