Turki Aljrees
Papers
2
Total Citations
36
H-Index
2
About
Turki Aljrees is a researcher specializing in robotics, artificial intelligence, and autonomous navigation systems. His work focuses on advancing the capabilities of wheeled mobile robots (WMRs) through stability analysis and sophisticated path planning techniques. Aljrees’s most impactful contribution is a comprehensive review of WMR stability and navigational methods, which has garnered 29 citations and serves as a foundational resource for researchers tackling navigation challenges in both static and dynamic environments. Building on this, his recent work introduces a novel deep reinforcement learning-based collision avoidance approach for robot path planning in unknown environments. This innovative method addresses critical limitations in current motion planning algorithms by leveraging reinforcement learning principles—action and reward mechanisms—to enable robots to learn and adapt to complex, unpredictable settings. By integrating deep learning with reinforcement learning, Aljrees is pushing the boundaries of how robots autonomously navigate and avoid obstacles without prior environmental knowledge. His research bridges theoretical stability analysis with practical, AI-driven navigation solutions, making significant strides toward more intelligent and adaptable robotic systems for real-world applications.
Research Focus
Key Achievements
Top Papers
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