  We propose a motion planner for cable-driven payload transportation using
multiple unmanned aerial vehicles (UAVs) in an environment cluttered with
obstacles. Our planner is kinodynamic, i.e., it considers the full dynamics
model of the transporting system including actuation constraints. Due to the
high dimensionality of the planning problem, we use a hierarchical approach
where we first solve the geometric motion planning using a sampling-based
method with a novel sampler, followed by constrained trajectory optimization
that considers the full dynamics of the system. Both planning stages consider
inter-robot and robot/obstacle collisions. We demonstrate in a
software-in-the-loop simulation and real flight experiments that there is a
significant benefit in kinodynamic motion planning for such payload transport
systems with respect to payload tracking error and energy consumption compared
to the standard methods of planning for the payload alone. Notably, we observe
a significantly higher success rate in scenarios where the team formation
changes are needed to move through tight spaces.
