Ciksadan

Papers

Total Citations

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About

Ciksadan is a researcher in robotics and computational intelligence, with a primary focus on fuzzy logic systems for autonomous navigation. Their key contributions lie in the comparative analysis of Type-1 and Interval Type-2 Fuzzy Logic Systems (T1FLS and IT2FLS) for mobile robot obstacle avoidance. In their most-cited work (2018, 6 citations), Ciksadan conducted MATLAB simulations to evaluate the performance of these fuzzy logic approaches across diverse environments, varying start-target configurations and obstacle densities. This research provides foundational insights into how different fuzzy logic types handle uncertainty in real-time path planning, offering practical guidance for selecting appropriate control strategies in autonomous robotics. While their citation count is modest, their work contributes to the ongoing refinement of fuzzy logic applications in mobile robotics, particularly in enhancing decision-making under ambiguous conditions. Ciksadan’s research bridges theoretical fuzzy logic concepts with tangible robotic implementations, making it relevant for students and engineers exploring intelligent control systems for autonomous vehicles and robots operating in dynamic, unpredictable settings.