This paper proposes RUR53: an Unmanned Ground Vehicle able to navigate through, identify, and reach areas of interest. There, it can recognize, localize, and manipulate work tools to perform both indoor and outdoor complex tasks. Indeed, a wide range of sensors composes the robot and enables it to perceive vast workspaces, reach distant targets, and face the uncertainties of the real world. Precise object detection is also guaranteed, essential to manipulate objects of different shapes and materials. Moreover, a customized 3-finger gripper makes the gripping mode suitable for any lightweight object. Two modalities are proposed: autonomous and teleoperated, letting both unskilled and skilled human operators easily adapt the system to complete personalized tasks. The paper exhaustively describes RUR53 architecture and demonstrates its good performance while executing both indoor and outdoor navigation and manipulation tasks. A specific case study is described where the proposed modular architecture allows to easily switch to a semi-teleoperated mode: the 2017 Mohamed Bin Zayed International Robotics Challenge, where our team ranked third in the Grand Challenge in collaboration with the Czech Technical University in Prague, the University of Pennsylvania, and the University of Lincoln (UK).

RUR53: an unmanned ground vehicle for navigation, recognition, and manipulation

Castaman, Nicola
;
Tosello, Elisa;Antonello, Morris;Bagarello, Nicola;Gandin, Silvia;Carraro, Marco;Munaro, Matteo;Bortoletto, Roberto;Ghidoni, Stefano;Menegatti, Emanuele;Pagello, Enrico
2020

Abstract

This paper proposes RUR53: an Unmanned Ground Vehicle able to navigate through, identify, and reach areas of interest. There, it can recognize, localize, and manipulate work tools to perform both indoor and outdoor complex tasks. Indeed, a wide range of sensors composes the robot and enables it to perceive vast workspaces, reach distant targets, and face the uncertainties of the real world. Precise object detection is also guaranteed, essential to manipulate objects of different shapes and materials. Moreover, a customized 3-finger gripper makes the gripping mode suitable for any lightweight object. Two modalities are proposed: autonomous and teleoperated, letting both unskilled and skilled human operators easily adapt the system to complete personalized tasks. The paper exhaustively describes RUR53 architecture and demonstrates its good performance while executing both indoor and outdoor navigation and manipulation tasks. A specific case study is described where the proposed modular architecture allows to easily switch to a semi-teleoperated mode: the 2017 Mohamed Bin Zayed International Robotics Challenge, where our team ranked third in the Grand Challenge in collaboration with the Czech Technical University in Prague, the University of Pennsylvania, and the University of Lincoln (UK).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3356080
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