Hybrid legged-wheeled robots are able to adapt their leg configuration and height to vary their footprint polygons and go over obstacles or traverse narrow spaces.  In this paper, we present a variable configuration wheeled motion planner based on the A* algorithm.  It takes advantage of the agility of hybrid wheeled-legged robots and plans paths over low-lying obstacles and in narrow spaces.  By imposing a symmetry on the robot polygon, the computed plans lie in a low-dimensional search space that provides the robot with configurations to safely negotiate obstacles by expanding or shrinking its footprint polygon.  The introduced autonomous planner is demonstrated using simulations and real-world experiments with the CENTAURO robot.