Most current systems capable of robotic object manipulation involve ad hoc assumptions about the order of operations necessary to achieve a task, and usually have no mechanism to predict how earlier decisions will affect the quality of the solution later. Solving this problem is sometimes referred to as combined task and motion planning. We propose that multi-step planning, a technique previously applied in some other domains, is an effective way to address the question of combined task and motion planning. We demonstrate the technique on a complex motion planning problem involving a two-armed robot (PR2) and an articulated object (folding chair) where our planner naturally discovers extra steps that are necessary to satisfy kinematic constraints of the problem. We also propose some further extensions to our algorithm that we believe will make it an extremely powerful technique in this domain.