RUR53: an Unmanned Ground Vehicle for Navigation, Recognition and Manipulation
Nicola Castaman, Elisa Tosello, Morris Antonello, Nicola Bagarello,, Silvia Gandin, Marco Carraro, Matteo Munaro, Roberto Bortoletto, Stefano, Ghidoni, Emanuele Menegatti, Enrico Pagello

TL;DR
This paper introduces RUR53, a modular autonomous ground vehicle capable of navigation, object recognition, and manipulation, demonstrated through indoor and outdoor tests, including a robotics challenge where it ranked third.
Contribution
The paper presents a novel modular architecture for an autonomous ground vehicle that integrates navigation, recognition, and manipulation capabilities with flexible software modules.
Findings
Successfully navigated and docked in front of a target object
Recognized and manipulated work tools like wrenches and valve stems
Ranked third in the 2017 Mohamed Bin Zayed International Robotics Challenge
Abstract
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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
