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  • 1.
    Gabellieri, Chiara
    et al.
    Centro di Ricerca “E. Piaggio” e Departimento di Ingnegneria dell’Informazione, Università di Pisa, Pisa, Italia.
    Palleschi, Alessandro
    Centro di Ricerca “E. Piaggio” e Departimento di Ingnegneria dell’Informazione, Università di Pisa, Pisa, Italia.
    Mannucci, Anna
    Centro di Ricerca “E. Piaggio” e Departimento di Ingnegneria dell’Informazione, Università di Pisa, Pisa, Italia.
    Pierallini, Michele
    Centro di Ricerca “E. Piaggio” e Departimento di Ingnegneria dell’Informazione, Università di Pisa, Pisa, Italia.
    Stefanini, Elisa
    Centro di Ricerca “E. Piaggio” e Departimento di Ingnegneria dell’Informazione, Università di Pisa, Pisa, Italia.
    Catalano, Manuel G.
    Istituto Italiano di Tecnologia, Genova GE, Italy.
    Caporale, Danilo
    Centro di Ricerca “E. Piaggio” e Departimento di Ingnegneria dell’Informazione, Università di Pisa, Pisa, Italia.
    Settimi, Alessandro
    Centro di Ricerca “E. Piaggio” e Departimento di Ingnegneria dell’Informazione, Università di Pisa, Pisa, Italia.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Magnusson, Martin
    Örebro University, School of Science and Technology.
    Garabini, Manolo
    Centro di Ricerca “E. Piaggio” e Departimento di Ingnegneria dell’Informazione, Università di Pisa, Pisa, Italia.
    Pallottino, Lucia
    Centro di Ricerca “E. Piaggio” e Departimento di Ingnegneria dell’Informazione, Università di Pisa, Pisa, Italia.
    Towards an Autonomous Unwrapping System for Intralogistics2019In: IEEE Robotics and Automation Letters, ISSN 2377-3766, E-ISSN 1949-3045, Vol. 4, no 4, p. 4603-4610Article in journal (Refereed)
    Abstract [en]

    Warehouse logistics is a rapidly growing market for robots. However, one key procedure that has not received much attention is the unwrapping of pallets to prepare them for objects picking. In fact, to prevent the goods from falling and to protect them, pallets are normally wrapped in plastic when they enter the warehouse. Currently, unwrapping is mainly performed by human operators, due to the complexity of its planning and control phases. Autonomous solutions exist, but usually they are designed for specific situations, require a large footprint and are characterized by low flexibility. In this work, we propose a novel integrated robotic solution for autonomous plastic film removal relying on an impedance-controlled robot. The main contribution is twofold: on one side, a strategy to plan Cartesian impedance and trajectory to execute the cut without damaging the goods is discussed; on the other side, we present a cutting device that we designed for this purpose. The proposed solution presents the characteristics of high versatility and the need for a reduced footprint, due to the adopted technologies and the integration with a mobile base. Experimental results are shown to validate the proposed approach.

    Download full text (pdf)
    Towards an Autonomous Unwrapping System for Intralogistics
  • 2.
    Mannucci, Anna
    et al.
    Research Center E. Piaggio, University of Pisa, Pisa, Italy.
    Pallottino, Lucia
    Research Center E. Piaggio, University of Pisa, Pisa, Italy.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Provably Safe Multi-Robot Coordination With Unreliable Communication2019In: IEEE Robotics and Automation Letters, ISSN 2377-3766, E-ISSN 1949-3045, Vol. 4, no 4, p. 3232-3239Article in journal (Refereed)
    Abstract [en]

    Coordination is a core problem in multi-robot systems, since it is a key to ensure safety and efficiency. Both centralized and decentralized solutions have been proposed, however, most assume perfect communication. This letter proposes a centralized method that removes this assumption, and is suitable for fleets of robots driven by generic second-order dynamics. We formally prove that: first, safety is guaranteed if communication errors are limited to delays; and second, the probability of unsafety is bounded by a function of the channel model in networks with packet loss. The approach exploits knowledge of the network's non-idealities to ensure the best possible performance of the fleet. The method is validated via several experiments with simulated robots.

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