  This paper presents a framework that allows online
dynamic-stability-constrained optimal trajectory planning of a mobile
manipulator robot working on rough terrain. First, the kinematics model of a
mobile manipulator robot, and the Zero Moment Point (ZMP) stability measure are
presented as theoretical background. Then, a sampling-based quasi-static
planning algorithm modified for stability guarantee and traction optimization
in continuous dynamic motion is presented along with a mathematical proof. The
robot's quasi-static path is then used as an initial guess to warm-start a
nonlinear optimal control solver which may otherwise have difficulties finding
a solution to the stability-constrained formulation efficiently. The
performance and computational efficiency of the framework are demonstrated
through an application to a simulated timber harvesting mobile manipulator
machine working on varying terrain. The results demonstrate feasibility of
online trajectory planning on varying terrain while satisfying the dynamic
stability constraint.
