  Mobile manipulation planning commonly adopts a decoupled approach that
performs planning separately on the base and the manipulator. While this
approach is fast, it can generate sub-optimal paths. Another direction is a
coupled approach jointly adjusting the base and manipulator in a
high-dimensional configuration space. This coupled approach addresses
sub-optimality and incompleteness of the decoupled approach, but has not been
widely used due to its excessive computational overhead. Given this trade-off
space, we present a simple, yet effective mobile manipulation sampling method,
harmonious sampling, to perform the coupled approach mainly in difficult
regions, where we need to simultaneously maneuver the base and the manipulator.
Our method identifies such difficult regions through a low-dimensional base
space by utilizing a reachability map given the target end-effector pose and
narrow passage detected by generalized Voronoi diagram. For the rest of simple
regions, we perform sampling mainly on the base configurations with a
predefined joint configuration, accelerating the planning process. We compare
our method with the decoupled and coupled approaches in six different problems
with varying difficulty. Our method shows meaningful improvements
experimentally in terms of time to find an initial solution (up to 5.6 times
faster) and final solution cost (up to 17% lower) over the decoupled approach,
especially in difficult scenes with narrow space. We also demonstrate these
benefits with a real, mobile Hubo robot.
