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About

Omar I. Dallal Bashi is a researcher specializing in autonomous systems, unmanned aerial vehicles (UAVs), and underwater robotics, with a focus on control systems, trajectory optimization, and environmental monitoring. His most cited work, "Unmanned Aerial Vehicle Quadcopter: A Review" (2017, 36 citations), provides a comprehensive overview of multicopter technology, highlighting its vertical take-off and landing (VTOL) capabilities and diverse civil and military applications, establishing a foundational resource for UAV research. He has advanced the field through innovative contributions such as trajectory optimization using nonlinear model predictive control to minimize fuel usage for underwater robots (2024, 8 citations), demonstrating practical applications in energy-efficient autonomous navigation. Additionally, his work on autonomous quadcopter altitude control for measuring hazardous gases (2018, 5 citations) addresses critical environmental monitoring challenges, while his development of object detection from 3D point clouds using Point-Pillars neural networks (2023, 3 citations) showcases expertise in deep learning for perception systems. Dallal Bashi’s research spans from foundational reviews to cutting-edge applications in robotics and AI, with a growing citation impact that underscores his contributions to autonomous vehicle technology and environmental safety.