The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

In microsurgery, a surgeon often deals with anatomical structures of sizes that are close to the limit of the human hand accuracy. Robotic assistants can help to push beyond the current state of practice by integrating imaging and robot-assisted tools. This paper demonstrates control of a handheld tremor reduction micromanipulator with visual servo techniques, aiding the operator by providing three behaviors: snap-to, motion-scaling, and standoff-regulation. A stereo camera setup viewing the workspace under high magnification tracks the tip of the micromanipulator and the desired target object being manipulated. Individual behaviors activate in task-specific situations when the micromanipulator tip is in the vicinity of the target. We show that the snap-to behavior can reach and maintain a position at a target with an accuracy of 17.5 ± 0.4 µm Root Mean Squared Error (RMSE) distance preventing unwanted contact with non-target objects also provides a larger margin of safety.

Notes

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, Sandrine Voros, Robert MacLachlan, Gregory Hager, and Cameron Riviere, "Active Guidance of a Handheld Micromanipulator using Visual Servoing," 2009 IEEE International Conference on Robotics and Automation, May, 2009, pp. 339 - 344.

BibTeX Reference

@inproceedings{Becker_2009_6448,
   author = "Brian Becker and Sandrine Voros and Robert MacLachlan and Gregory Hager and Cameron Riviere",
   title = "Active Guidance of a Handheld Micromanipulator using Visual Servoing",
   booktitle = "2009 IEEE International Conference on Robotics and Automation",
   pages = "339 - 344",
   month = "May",
   year = "2009",
}

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