About

Mohammad Al-Jarrah is a pioneering roboticist whose research spans modular self-reconfigurable robotics, mobile robot navigation, and intelligent sensor fusion. His most influential work, "A Novel Edge Detection Algorithm for Mobile Robot Path Planning" (2018, 46 citations), introduced a groundbreaking hybrid approach combining fuzzy image processing with bacterial algorithms to dramatically improve vision system efficiency and computational speed for real-time robot navigation. Al-Jarrah's foundational contributions to modular robotics include the design and implementation of HexBot, a planar hexagonal modular self-reconfigurable robotic system, where he developed reconfiguration path planners that determine optimal sequences of module movements for shape transformation. His work extends to wireless sensor networks, where he proposed joint location and orientation estimation algorithms using directional antennas for mobile robots. Al-Jarrah has also explored diverse applications including EMG-controlled industrial robotic arms, blimp robot tracking via visual fuzzy servoing, and 3D environment modeling using mono-vision systems. His research demonstrates a consistent commitment to creating intelligent, adaptive robotic systems that can perceive, navigate, and reconfigure in complex environments, making significant contributions to both theoretical foundations and practical implementations in robotics.

Research Focus

Key Achievements

4
H-Index
8
Papers
81
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
A Novel Edge Detection Algorithm for Mobile Robot Path Planning
46 citations · 2018
📈 Most Prolific Year: 2009 (2 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: Khalifa University of Science and Technology, University of Manchester, American University of Sharjah, Yarmouk University, Prince Sattam Bin Abdulaziz University, Jordan University of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago