  In this paper, we propose a whole-body planning framework that unifies
dynamic locomotion and manipulation tasks by formulating a single multi-contact
optimal control problem. We model the hybrid nature of a generic multi-limbed
mobile manipulator as a switched system, and introduce a set of constraints
that can encode any pre-defined gait sequence or manipulation schedule in the
formulation. Since the system is designed to actively manipulate its
environment, the equations of motion are composed by augmenting the robot's
centroidal dynamics with the manipulated-object dynamics. This allows us to
describe any high-level task in the same cost/constraint function. The
resulting planning framework could be solved on the robot's onboard computer in
real-time within a model predictive control scheme. This is demonstrated in a
set of real hardware experiments done in free-motion, such as base or
end-effector pose tracking, and while pushing/pulling a heavy resistive door.
Robustness against model mismatches and external disturbances is also verified
during these test cases.
