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Control framework of the ROBILAUT soil sampling robot: system overview and experimental results

Part of: The 40th Anniversary of Robotica

Published online by Cambridge University Press:  23 May 2024

Daniele Di Vito Open the ORCID record for Daniele Di Vito [Opens in a new window] ,
Paolo Di Lillo Open the ORCID record for Paolo Di Lillo [Opens in a new window] ,
Filippo Arrichiello Open the ORCID record for Filippo Arrichiello [Opens in a new window] ,
Cesare Ferone ,
Raffaele Amico  and
Gianluca Antonelli Open the ORCID record for Gianluca Antonelli [Opens in a new window]
Daniele Di Vito*
Affiliation:
Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Cassino, Italy
Paolo Di Lillo
Affiliation:
Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Cassino, Italy
Filippo Arrichiello
Affiliation:
Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Cassino, Italy
Cesare Ferone
Affiliation:
Natura srl, Casoria, Italy
Raffaele Amico
Affiliation:
OCIMA srl, Caivano, Italy
Gianluca Antonelli
Affiliation:
Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Cassino, Italy
*
Corresponding author: Daniele Di Vito; Email: daniele.divito@unicas.it
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Abstract

The paper presents the control architecture of a crawler mobile robot designed and developed to sample potentially contaminated lands. The robot, developed in the framework of an Italian national project named ROBILAUT, carries a driller with a customized sampling mechanism to implement on-site the required quartering, and it is controlled to move the drilling device on specific points acquired in real time before the mission starts. The paper describes the software architecture for the navigation and control, focusing on the control framework of the robotic platform. Specifically, the robot exhibits a differential drive kinematics with actuators’ constraints, and two different control strategies have been experimentally tested for comparison both in a structured environment and in the real site in May 2023.

Keywords

mobile roboticsfield roboticsnonlinear controlmodel predictive controlenvironmental soil sampling
Type
Research Article
Information
Robotica , First View , pp. 1 - 16
Copyright
© The Author(s), 2024. Published by Cambridge University Press

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