Abdullah-Al Nahid
Papers
8
Total Citations
248
H-Index
7
About
Abdullah-Al Nahid is a researcher whose work sits at the intersection of robotics, artificial intelligence, and biomedical engineering. His primary research areas include autonomous navigation, reinforcement learning for robotics, and the analysis of biosignals for prosthetic control. Nahid’s major contributions span from foundational work in autonomous vacuum cleaner path planning (82 citations) to the development of a systematic review on reinforcement learning-based robotics (46 citations), which has become a key reference for researchers entering the field. He has also advanced practical applications such as line-following robots (44 citations) and color-based multi-destination robots (39 citations), demonstrating a consistent focus on intelligent, sensor-driven automation. Notably, his work on finger movement classification using surface EMG signals (15 citations) bridges robotics and healthcare, contributing to the development of more natural prosthetic control. More recently, Nahid has applied AI and robotics to infrastructure maintenance with an automated pavement-crack-evaluation system (11 citations). His diverse portfolio—from household robots to biomedical signal processing—reflects a commitment to creating autonomous systems that solve real-world problems, making his research both impactful and accessible to students and practitioners alike.
Research Focus
Key Achievements
Top Papers
- 1Path planning algorithm development for autonomous vacuum cleaner robots82 citations · 2014
- 2
- 3Implementation of autonomous line follower robot44 citations · 2012
- 4Sensor based autonomous color line follower robot with obstacle avoidance39 citations · 2013
- 5
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- 7Implementation of vision based object tracking robot9 citations · 2012
- 8SMART HUMAN FOLLOWING BABY STROLLER USING COMPUTER VISION2 citations · 2022