Majid Deldar

Papers

Total Citations

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About

Majid Deldar is a researcher whose work lies at the intersection of robotics and intelligent control systems, with a particular focus on autonomous navigation. His most-cited paper, "AGV Path Planning in Unknown Environment Using Fuzzy Inference Systems" (2006, 8 citations), addresses a fundamental challenge in mobile robotics: enabling automated guided vehicles (AGVs) to navigate safely through unfamiliar environments. In this work, Deldar proposed a novel approach that leverages fuzzy control techniques to guide wheeled mobile robots without requiring a pre-mapped environment, allowing them to react adaptively to obstacles in real time. This contribution is especially relevant to the broader fields of industrial automation and logistics, where AGVs are increasingly deployed. While his citation count reflects a niche but impactful contribution, Deldar’s work represents an early and practical application of fuzzy logic to path planning—a problem that remains central to robotics research today. His research offers a clear, implementable solution for engineers and students interested in merging soft computing with autonomous vehicle control, demonstrating how fuzzy inference systems can provide robust, human-like decision-making in uncertain, dynamic settings.