  Fast, robust, and flexible part feeding is essential for enabling automation
of low volume, high variance assembly tasks. An actuated vision-based solution
on a traditional vibratory feeder, referred to here as a vision trap, should in
principle be able to meet these demands for a wide range of parts. However, in
practice, the flexibility of such a trap is limited as an expert is needed to
both identify manageable tasks and to configure the vision system. We propose a
novel approach to vision trap design in which the identification of manageable
tasks is automatic and the configuration of these tasks can be delegated to an
automated feeder design system. We show that the trap's capabilities can be
formalized in such a way that it integrates seamlessly into the ecosystem of
automated feeder design. Our results on six canonical parts show great promise
for autonomous configuration of feeder systems.
