  Remotely programming robots to execute tasks often relies on registering
objects of interest in the robot's environment. Frequently, these tasks involve
articulating objects such as opening or closing a valve. However, existing
human-in-the-loop methods for registering objects do not consider articulations
and the corresponding impact to the geometry of the object, which can cause the
methods to fail. In this work, we present an approach where the registration
system attempts to automatically determine the object model, pose, and
articulation for user-selected points using nonlinear fitting and the iterative
closest point algorithm. When the fitting is incorrect, the operator can
iteratively intervene with corrections after which the system will refit the
object. We present an implementation of our fitting procedure for one
degree-of-freedom (DOF) objects with revolute joints and evaluate it with a
user study that shows that it can improve user performance, in measures of time
on task and task load, ease of use, and usefulness compared to a manual
registration approach. We also present a situated example that integrates our
method into an end-to-end system for articulating a remote valve.
