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About

Mohammad A. Jaradat is a prominent robotics and autonomous systems researcher whose work has fundamentally advanced mobile robot navigation, localization, and intelligent control. With a career spanning over a decade, his research sits at the intersection of artificial intelligence, sensor fusion, and practical robotic applications, garnering more than 700 citations across his most influential publications. Jaradat's earliest and most impactful contributions — his 2010 reinforcement learning-based navigation framework (210 citations) and his 2011 hybrid fuzzy potential field approach (112 citations) — established him as a leading voice in autonomous robot motion planning within dynamic environments. His work consistently bridges theoretical rigor with real-world utility, exemplified by his development of a portable solar panel cleaning robot and an in-pipe leak detection system incorporating neural networks, addressing pressing industrial challenges in renewable energy and oil and gas infrastructure. His research in pipeline inspection gauge navigation and multi-sensor fusion using Extended Kalman Filtering further demonstrates a sophisticated command of inertial navigation and probabilistic localization methods. His 2020 RRT*N algorithm offers an efficient, robust solution for 3D path planning in both static and dynamic settings. Across these contributions, Jaradat has distinguished himself as a versatile engineer-scientist whose innovations carry meaningful real-world consequence.