  In logistics warehouse, since many objects are randomly stacked on shelves,
it becomes difficult for a robot to safely extract one of the objects without
other objects falling from the shelf. In previous works, a robot needed to
extract the target object after rearranging the neighboring objects. In
contrast, humans extract an object from a shelf while supporting other
neighboring objects. In this paper, we propose a bimanual manipulation planner
based on collapse prediction trained with data generated from a physics
simulator, which can safely extract a single object while supporting the other
object. We confirmed that the proposed method achieves more than 80% success
rate for safe extraction by real-world experiments using a dual-arm
manipulator.
