Centralized Model Predictive Control for Collaborative Loco-Manipulation

In this work, we extend the model predictive control methods developed in the legged robotics literature to collaborative loco-manipulation settings. The systems we study entail a payload collectively carried by multiple quadruped robots equipped with a mechanical arm. We use a direct multiple shooting method to solve the resulting high-dimensional, optimal control problems for trajectories of ground reaction forces, manipulation wrenches, and stepping locations. To capture the dominant dynamics of the system, we model each agent and the shared payload as single rigid bodies. We demonstrate the versatility of our framework in a series of simulation experiments involving collaborative manipulation over challenging terrains.