The diffusion of e-commerce has produced larger and larger volumes of varying items to be handled in warehouses, with the effect that the need for picking automation is increasing. Conventionally, automation has been achieved through a custom plant designed for large-scale production of items having well-established characteristics that are expected to change slowly and to only a small degree over time. However, today the challenge is to realize a solution that is flexible enough to handle goods with different shapes, sizes, and physical properties and that require different grasping modes. To solve this problem, we first analyzed how humans perform picking and then synthesized their behavior according to four main tactics. These were then used as guidelines for the design, planning, and control of WRAPP-up, a dual-arm robot composed of two anthropomorphic manipulators: a Pisa/IIT SoftHand and a velvet tray (Figure 1). The system has been validated and evaluated through extensive experimental tests.