Papers
18
Total Citations
193
H-Index
7
About
Muhammad Attamimi is a versatile robotics and intelligent systems researcher whose work spans human-robot interaction, computer vision, and smart technology applications. He is perhaps best known for his pioneering investigations into child-robot relationships, exploring how robots can build meaningful bonds with children — particularly shy or introverted individuals — through personality-aware play strategies and physical touch such as hand-holding. These studies, accumulating over 50 citations combined, have meaningfully advanced our understanding of social robotics in educational and therapeutic contexts. Attamimi has also made significant contributions to robot perception, developing a real-time 3D visual sensor system that integrates depth and color data for robust object recognition (30 citations), and designing visual recognition frameworks enabling humanoid robots to perform practical cleaning tasks. His work on multimodal learning allows robots to acquire knowledge of novel objects through combined audio-visual input — a critical capability for home assistant robots. Beyond robotics, Attamimi has demonstrated broad engineering impact through practical innovations including an Android-based smart trolley system (28 citations) and a LIDAR-equipped mobile robot for gas leak inspection. His research consistently bridges theoretical intelligence with real-world deployment, making him a notable contributor across robotics, human-computer interaction, and applied sensing systems.
Research Focus
Key Achievements
Top Papers
- 1Toward playmate robots that can play with children considering personality33 citations · 2014
- 2Real-time 3D visual sensor for robust object recognition30 citations · 2010
- 3Development of Smart Trolley System Based on Android Smartphone Sensors28 citations · 2019
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- 6Visual Recognition System for Cleaning Tasks by Humanoid Robots17 citations · 2013
- 7Attention Estimation for Child-Robot Interaction7 citations · 2016
- 8Line Follower Smart Trolley System V2 using RFID6 citations · 2021
- 9Gas Leak Inspection System Using Mobile Robot Equipped With LIDAR5 citations · 2021
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