Reda Elbasiony
Tanta University, Egypt-Japan University of Science and Technology
Papers
2
Total Citations
37
H-Index
2
About
Reda Elbasiony’s research bridges robotics, human-robot interaction, and intelligent localization, with a focus on enabling machines to learn from and navigate alongside humans. His most cited work, “Humanoids skill learning based on real-time human motion imitation using Kinect” (25 citations), pioneers a framework where humanoid robots acquire complex motor skills by observing and mimicking human movements in real time—a foundational step toward more intuitive human-robot collaboration. In parallel, his paper “WiFi Localization for Mobile Robots Based on Random Forests and GPLVM” (12 citations) addresses the challenge of indoor robot navigation by fusing machine learning techniques with ubiquitous WiFi signals, offering a robust, infrastructure-light alternative to GPS. Together, these contributions demonstrate Elbasiony’s ability to combine perception, learning, and control, advancing both the autonomy of mobile robots and the naturalness of human-robot teaching. His work is particularly notable for its practical, real-world focus—using accessible sensors like the Kinect and leveraging existing WiFi networks—making it highly relevant for researchers in service robotics, assistive technology, and intelligent environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2WiFi Localization for Mobile Robots Based on Random Forests and GPLVM12 citations · 2014