  Mobile robots, performing long-term manipulation activities in human
environments, have to perceive a wide variety of objects possessing very
different visual characteristics and need to reliably keep track of these
throughout the execution of a task. In order to be efficient, robot perception
capabilities need to go beyond what is currently perceivable and should be able
to answer queries about both current and past scenes. In this paper we
investigate a perception system for long-term robot manipulation that keeps
track of the changing environment and builds a representation of the perceived
world. Specifically we introduce an amortized component that spreads perception
tasks throughout the execution cycle. The resulting query driven perception
system asynchronously integrates results from logged images into a symbolic and
numeric (what we call sub-symbolic) representation that forms the perceptual
belief state of the robot.
