We present an initial demonstration of dexterous mobility using the uBot-5, a dynamically balancing mobile manipulator. Dexterous mobility refers generally to a level of bodily resourcefulness that permits the autonomous reassignment of effectors for the purpose of maintaining mobility in a variety of situations. We begin by describing a set of postural stability controllers in terms of a small number of simple control objectives. We then show how the resulting postures support dexterous mobility by enabling a new ldquoknuckle walkingrdquo mobility mode. In a preliminary experiment, we develop this mobility mode by formulating a practical reinforcement learning problem that allows the robot to learn an efficient gait on-line in a single trial.