  We present a novel approach for mobile manipulator self-calibration using
contact information. Our method, based on point cloud registration, is applied
to estimate the extrinsic transform between a fixed vision sensor mounted on a
mobile base and an end effector. Beyond sensor calibration, we demonstrate that
the method can be extended to include manipulator kinematic model parameters,
which involves a non-rigid registration process. Our procedure uses on-board
sensing exclusively and does not rely on any external measurement devices,
fiducial markers, or calibration rigs. Further, it is fully automatic in the
general case. We experimentally validate the proposed method on a custom mobile
manipulator platform, and demonstrate centimetre-level post-calibration
accuracy in positioning of the end effector using visual guidance only. We also
discuss the stability properties of the registration algorithm, in order to
determine the conditions under which calibration is possible.
