Mohammad R. Alenezi
Papers
3
Total Citations
37
H-Index
2
About
Mohammad R. Alenezi is a robotics researcher dedicated to enhancing autonomous systems for critical real-world applications, particularly in search and rescue and remote sensing. His work focuses on developing intelligent control and path planning algorithms for unmanned vehicles operating in hazardous and dynamic environments. Alenezi’s most impactful contribution is his pioneering work on autonomous quadrotor landing, where he designed a vision-based neural network controller enabling a drone to land safely on moving targets—a breakthrough for time-sensitive disaster response. This paper has earned 28 citations, reflecting its significance in the field. He has also advanced optimal path planning for unmanned ground vehicles in hazardous indoor settings (7 citations) and developed intelligent hybrid fuzzy controllers for differential drive robots using bio-inspired optimization algorithms. Collectively, his research bridges computer vision, neural networks, and control theory to create robust, autonomous solutions that assist first responders in life-saving missions. Alenezi’s work stands out for its direct application to pressing societal challenges, making him a notable contributor to the future of intelligent robotics in emergency scenarios.
Research Focus
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Top Papers
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