  We address the problem of motion planning for a robotic manipulator with the
task to place a grasped object in a cluttered environment. In this task, we
need to locate a collision-free pose for the object that a) facilitates the
stable placement of the object, b) is reachable by the robot manipulator and c)
optimizes a user-given placement objective. Because of the placement objective,
this problem is more challenging than classical motion planning where the
target pose is defined from the start. To solve this task, we propose an
anytime algorithm that integrates sampling-based motion planning for the robot
manipulator with a novel hierarchical search for suitable placement poses. We
evaluate our approach on a dual-arm robot for two different placement
objectives, and observe its effectiveness even in challenging scenarios.
