  This paper presents a task and motion planning (TAMP) framework for a robotic
manipulator in order to retrieve a target object from clutter. We consider a
configuration of objects in a confined space with a high density so no
collision-free path to the target exists. The robot must relocate some objects
to retrieve the target without collisions. For fast completion of object
rearrangement, the robot aims to optimize the number of pick-and-place actions
which often determines the efficiency of a TAMP framework.
  We propose a task planner incorporating motion planning to generate
executable plans which aims to minimize the number of pick-and-place actions.
In addition to fully known and static environments, our method can deal with
uncertain and dynamic situations incurred by occluded views. Our method is
shown to reduce the number of pick-and-place actions compared to baseline
methods (e.g., at least 28.0% of reduction in a known static environment with
20 objects).
