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Carnegie Mellon Robotics Institute

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Abstract

This paper presents the development of an inverse kinematic model for a flexure-based micromanipulator using a feedforward neural network. The manipulator is part of an active handheld instrument designed to cancel hand tremor during microsurgery. The manipulator is actuated using three piezoelectric stacks. Preliminary results yield a mean squared error of 5% of the total stack range of motion, and a maximum error of 14% of the total range of motion.

Notes

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

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

Associated Project(s): Micron: Intelligent Microsurgical Instruments

Number of pages: 3

Text Reference

J.G. Avedillo, David Choi, and Cameron Riviere, "Inverse Kinematic Model of Flexure-Based Microsurgical Manipulator," Proceedings of the 27th Annual International Conference of the Engineering in Medicine and Biology Society (EMBS 2005), September, 2005, pp. 5775 - 5777.

BibTeX Reference

@inproceedings{Choi_2005_5616,
   author = "J.G. Avedillo and David Choi and Cameron Riviere",
   title = "Inverse Kinematic Model of Flexure-Based Microsurgical Manipulator",
   booktitle = "Proceedings of the 27th Annual International Conference of the Engineering in Medicine and Biology Society (EMBS 2005)",
   pages = "5775 - 5777",
   month = "September",
   year = "2005",
}

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