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.
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