  This paper discusses a new approach for determining the calibration
parameters of independently-actuated optical fibers in multi-object
astronomical fiber positioning systems. This work comes from the development of
a new type of piezoelectric motor intended to enhance the 'tilting spine' fiber
positioning technology originally created by the Australian Astronomical
Observatory. Testing has shown that the motor's performance can vary depending
on the fiber's location within its accessible field, meaning that an individual
fiber is difficult calibrate with a one-time routine. Better performance has
resulted from constantly updating calibration parameters based on the observed
movements of the fiber during normal closed-loop positioning. Over time,
location-specific historical data is amassed that can be used to better predict
the results of a future fiber movement. This is similar to a technique
previously proposed by the Australian Astronomical Observatory, but with the
addition of location-specific learning. Results from a prototype system are
presented, showing a significant reduction in overall positioning error when
using this new approach.
