Papers
17
Total Citations
194
H-Index
10
About
Sevil Ahmed is a robotics and autonomous systems researcher whose work spans mobile robot control, human-robot interaction, and intelligent sensing technologies. Her research addresses some of the most pressing challenges in modern robotics, including trajectory tracking under uncertainty, target recognition, and seamless human-machine collaboration. Ahmed's contributions to intelligent control are exemplified by her development of a Type-2 Fuzzy-Neural PID controller for mobile robot trajectory tracking, her most-cited work with 23 citations, which tackles real-world uncertainty in autonomous navigation. Her parallel investigations into target detection and following — leveraging Microsoft Kinect, 2D LiDAR, and deep convolutional neural networks — have collectively accumulated nearly 55 citations, establishing her as a significant voice in perception-driven autonomy. Particularly noteworthy is her pioneering work in gesture-based human-robot interfaces, using Leap Motion and Kinect sensors to enable intuitive control of both mobile robots and manipulators. She has also explored emerging frontiers, including blockchain-enabled multi-agent robotic systems and MQTT cloud-based robotized wireless sensor networks for environmental monitoring. Across her portfolio, Ahmed consistently bridges theoretical innovation with real-world application, making her research highly relevant to students and practitioners developing next-generation intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Trajectory Control of Mobile Robots using Type-2 Fuzzy-Neural PID Controller23 citations · 2015
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- 5A robotized wireless sensor network based on MQTT cloud computing14 citations · 2017
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- 7Environmental monitoring using a robotized wireless sensor network13 citations · 2018
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