An automated picking workstation for healthcare applications

  • Authors:

  • Paolo Piccinini;Rita Gamberini;Andrea Prati;Bianca Rimini;Rita Cucchiara

  • Affiliations:

  • Department of Information Engineering, University of Modena and Reggio Emilia, Via Vignolese, 905/b, Modena, Italy;Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia, Via Amendola, 2, Padiglione Morselli, Reggio Emilia, Italy;Department of Design and Planning in Complex Environments, University IUAV of Venezia, Santa Croce 1957, Venezia, Italy;Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia, Via Amendola, 2, Padiglione Morselli, Reggio Emilia, Italy;Department of Information Engineering, University of Modena and Reggio Emilia, Via Vignolese, 905/b, Modena, Italy

  • Venue:
  • Computers and Industrial Engineering
  • Year:
  • 2013

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Abstract

The costs associated with the management of healthcare systems have been subject to continuous scrutiny for some time now, with a view to reducing them without affecting the quality as perceived by final users. A number of different solutions have arisen based on centralisation of healthcare services and investments in Information Technology (IT). One such example is centralised management of pharmaceuticals among a group of hospitals which is then incorporated into the different steps of the automation supply chain. This paper focuses on a new picking workstation available for insertion in automated pharmaceutical distribution centres and which is capable of replacing manual workstations and bringing about improvements in working time. The workstation described uses a sophisticated computer vision algorithm to allow picking of very diverse and complex objects randomly available on a belt or in bins. The algorithm exploits state-of-the-art feature descriptors for an approach that is robust against occlusions and distracting objects, and invariant to scale, rotation or illumination changes. Finally, the performance of the designed picking workstation is tested in a large experimentation focused on the management of pharmaceutical items.