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Fuzzy logic control strategy for improved traction and maneuverability in modular articulated robots

Published online by Cambridge University Press:  21 July 2025

Simone Pantanetti Open the ORCID record for Simone Pantanetti [Opens in a new window] ,
Andrea Botta Open the ORCID record for Andrea Botta [Opens in a new window] ,
Giacomo Palmieri  and
Giuseppe Quaglia
Simone Pantanetti*
Affiliation:
Department of Industrial Engineering and Mathematical Sciences, Polytechnic University of Marche, Ancona, Italy
Andrea Botta
Affiliation:
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Torino, Italy
Giacomo Palmieri
Affiliation:
Department of Industrial Engineering and Mathematical Sciences, Polytechnic University of Marche, Ancona, Italy
Giuseppe Quaglia
Affiliation:
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Torino, Italy
*
Corresponding author: Simone Pantanetti; Email: s.pantanetti@pm.univpm.it
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Abstract

This paper presents the design, control strategy, and preliminary testing of Epi.Q, a modular unmanned vehicle (UGV) tailored for challenging environments, including exploration and surveillance tasks. To manage the complexities of the articulated structure, including lateral slip and the risk of jackknifing, a fuzzy logic-based traction control system was implemented. To improve traction stability by modulating power distribution between modules, the system optimally controls steering and traction. Subsequently, the paper introduces the fuzzy control system and presents preliminary validation experiments, including hill-climbing, obstacle navigation, steering, and realignment tests. Preliminary results indicate that the proposed fuzzy control strategy significantly improves traction and maneuverability even on steep inclines and uneven surfaces. These findings highlight the potential for fuzzy logic control to improve UGV performance.

Keywords

fuzzy logic controlarticulated vehicleUGVtraction allocationobstacle climbing

Information

Type
Research Article
Information
Robotica , First View , pp. 1 - 22
Copyright
© The Author(s), 2025. Published by Cambridge University Press

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