  Dexterous manipulation tasks often require contact switching, where fingers
make and break contact with the object. We propose a method that plans
trajectories for dexterous manipulation tasks involving contact switching using
contact-implicit trajectory optimization (CITO) augmented with a high-level
discrete contact sequence planner. We first use the high-level planner to find
a sequence of finger contact switches given a desired object trajectory. With
this contact sequence plan, we impose additional constraints in the CITO
problem. We show that our method finds trajectories approximately 7 times
faster than a general CITO baseline for a four-finger planar manipulation
scenario. Furthermore, when executing the planned trajectories in a full
dynamics simulator, we are able to more closely track the object pose
trajectories planned by our method than those planned by the baselines.
