  Robots that autonomously manipulate objects within warehouses have the
potential to shorten the package delivery time and improve the efficiency of
the e-commerce industry. In this paper, we present a robotic system that is
capable of both picking and placing general objects in warehouse scenarios.
Given a target object, the robot autonomously detects it from a shelf or a
table and estimates its full 6D pose. With this pose information, the robot
picks the object using its gripper, and then places it into a container or at a
specified location. We describe our pick-and-place system in detail while
highlighting our design principles for the warehouse settings, including the
perception method that leverages knowledge about its workspace, three grippers
designed to handle a large variety of different objects in terms of shape,
weight and material, and grasp planning in cluttered scenarios. We also present
extensive experiments to evaluate the performance of our picking system and
demonstrate that the robot is competent to accomplish various tasks in
warehouse settings, such as picking a target item from a tight space, grasping
different objects from the shelf, and performing pick-and-place tasks on the
table.
