This paper presents a novel method to control humanoid robot dynamic
loco-manipulation with multiple contact modes via Multi-contact Model
Predictive Control (MPC) framework. In this framework, we proposed a
multi-contact dynamics model that can represent different contact modes in
loco-manipulation (e.g., hand contact with object and foot contacts with
ground). The proposed dynamics model simplifies the object dynamics as external
force applied to the system (external force model) to ensure the simplicity and
feasibility of the MPC problem. In numerical validations, our Multi-contact MPC
framework only needs contact timings of each task and desired states to give
MPC the knowledge of changes in contact modes in the prediction horizons in
loco-manipulation. The proposed framework can control the humanoid robot to
complete multi-tasks dynamic loco-manipulation applications such as efficiently
picking up and dropping off objects while turning and walking.Comment: 6 pages, 7 figures, submitted to L-CSS and ACC 202