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

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.