Complex object manipulation with hierarchical optimal control

This paper develops a hierarchical model predictive optimal control solution to the complex and interesting problem of object manipulation. Controlling an object through external manipulators is challenging, involving nonlinearities, redundancy, high dimensionality, contact breaking, underactuation, and more. Manipulation can be framed as essentially the same problem as locomotion (with slightly different parameters). Significant progress has recently been made on the locomotion problem. We develop a methodology to address the challenges of manipulation, extending the most current solutions to locomotion and solving the problem fast enough to run in a realtime implementation. We accomplish this by breaking up the single difficult problem into smaller more tractable problems. Results are presented supporting this method.