Hafiz Rashidi Ramli
Papers
13
Total Citations
255
H-Index
8
About
Hafiz Rashidi Ramli is a versatile robotics and intelligent systems researcher whose work spans computer vision, autonomous robotics, rehabilitation engineering, and agricultural automation. He has made particularly significant contributions to the palm oil industry, developing AI-driven detection systems for oil palm fresh fruit bunch (FFB) ripeness assessment using YOLOv4, a body of work that has collectively garnered over 100 citations and directly addresses Malaysia's critical agricultural labour shortage. His 2022 real-time ripeness detection study alone has accumulated 49 citations, reflecting its practical impact on maximising oil extraction rates through automated harvesting. Beyond agriculture, Ramli has contributed meaningfully to medical robotics and rehabilitation technology, including a well-cited review of shape memory alloy actuators for upper limb prostheses and assistive devices (44 citations), and a scoping review of stroke rehabilitation technologies in Southeast Asia. His earlier foundational work on vision-based line-following mobile robots (2009, 41 citations) demonstrates a career built on applied robotics innovation. More recently, he has explored deep reinforcement learning for dynamic robot navigation, robotic gripper optimization, and surgical image segmentation, positioning himself as a broad contributor to intelligent robotics systems with real-world humanitarian and industrial relevance.
Research Focus
Key Achievements
Top Papers
- 1Real-Time Detection of Ripe Oil Palm Fresh Fruit Bunch Based on YOLOv449 citations · 2022
- 2Shape memory alloys actuated upper limb devices: A review44 citations · 2023
- 3Vision-based system for line following mobile robot41 citations · 2009
- 4Oil Palm Fresh Fruit Bunch Ripeness Detection Methods: A Systematic Review37 citations · 2023
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