CMU-CS-22-130 Computer Science Department School of Computer Science, Carnegie Mellon University
Low-Latency Metallic Interference Rejection Alex Tarng M.S. Thesis December 2022
The Micron is an active handheld micromanipulator designed for membrane-peeling procedures for use in retinal surgery. The tool performs hand tremor compensation by deflecting the tip of the tool to reduce damage to the retina during microsurgery. In order to accomplish this, the control system must have a precise, low-latency measurement of the 6 degree-of-freedom pose of the tool's body. This is done via electromagnetic tracking; however, this approach is susceptible to metallic interference, disturbing the pose measurement when using a high sample rate. By using multiple carrier frequencies, the tracker can acquire both low latency data with a high frequency carrier and data less susceptible to metal interference with a low frequency carrier. This research formulates and implements a novel dual-rate compensation method which combines high and low frequency data using a pair of unscented Kalman filters to reject metallic interference. We also provide some preliminary evaluation of the system by showing metallic interference rejection in simple test cases and discuss the viability of using this scheme in a real-time control system.
32 pages
Thesis Committee:
Srinivasan Seshan, Head, Computer Science Department
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