Tulus Tulus

Papers

Total Citations

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About

Tulus Tulus is a researcher whose work centers on the application of intelligent control systems for mobile robotics, with a particular focus on fuzzy logic and sensor fusion. His major contributions lie in advancing the stability and autonomous navigation of robots in complex, unknown environments. Notably, his 2018 paper on controlling the motion stability of a line tracer robot using fuzzy logic and a Kalman filter (4 citations) addresses the challenging task of maintaining a two-wheeled robot in an upright position while it follows a predefined path, a critical problem in balancing robotics. Earlier, in 2014, he designed a behavior-based architecture using fuzzy logic for navigating car-like mobile robots in unfamiliar settings (3 citations), integrating goal-seeking, obstacle avoidance, and backward movement behaviors. While his citation counts are modest, Tulus’s work is foundational for students and researchers exploring low-cost, practical implementations of fuzzy control in robotics. His research demonstrates a hands-on approach to solving real-world navigation and stability issues, making it a valuable reference for those entering the field of autonomous systems.