The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

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.

Keywords

medical robotics, microsurgery, virtual fixtures

Notes

Sponsor: NIH, American Society for Laser Medicine and Surgery, NSF, ARCS Foundation

Associated Center(s) / Consortia: Medical Robotics Technology Center

Associated Lab(s) / Group(s): Surgical Mechatronics Laboratory

Associated Project(s): Micron: Intelligent Microsurgical Instruments

Text Reference

Brian Becker, Robert MacLachlan, Gregory Hager, and Cameron Riviere, "Handheld micromanipulation with vision-based virtual fixtures," Proc. IEEE International Conference on Robotics and Automation, May, 2011, pp. 4127-4132.

BibTeX Reference

@inproceedings{Becker_2011_6919,
   author = "Brian Becker and Robert MacLachlan and Gregory Hager and Cameron Riviere",
   title = "Handheld micromanipulation with vision-based virtual fixtures",
   booktitle = "Proc. IEEE International Conference on Robotics and Automation",
   pages = "4127-4132",
   month = "May",
   year = "2011",
}

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