Paper

RUR53: an Unmanned Ground Vehicle for Navigation, Recognition and Manipulation

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

2020

Overview

This paper proposes RUR53: an Unmanned Ground Vehicle able to autonomously navigate through, identify, and reach areas of interest; and there recognize, localize, and manipulate work tools to perform complex manipulation tasks. The proposed contribution includes a modular software architecture where each module solves specific sub-tasks and that can be easily enlarged to satisfy new requirements. Included indoor and outdoor tests demonstrate the capability of the proposed system to autonomously detect a target object (a panel) and precisely dock in front of it while avoiding obstacles. They show it can autonomously recognize and manipulate target work tools (i.e., wrenches and valve stems) to accomplish complex tasks (i.e., use a wrench to rotate a valve stem). A specific case study is described where the proposed modular architecture lets easy switch to a semi-teleoperated mode. The paper exhaustively describes description of both the hardware and software setup of RUR53, its performance when tests at the 2017 Mohamed Bin Zayed International Robotics Challenge, and the lessons we learned when participating at this competition, where we ranked third in the Gran Challenge in collaboration with the Czech Technical University in Prague, the University of Pennsylvania, and the University of Lincoln (UK).

• Publisher: Cornell University Library, arXiv.org
• Subject: Algorithms / Colleges & universities / Modularity / Recognition / Robot arms / Robotics / Unmanned ground vehicles