Muhamad Yusvin Mustar
Papers
6
Total Citations
18
H-Index
2
About
Muhamad Yusvin Mustar is a robotics researcher focused on human-robot interaction, autonomous navigation, and educational robotics. His work bridges the gap between intuitive control systems and practical robotic applications, with a particular emphasis on child-robot interaction in educational settings—a field where his 2022 paper outlines both the potential and challenges of using user interfaces to enhance learning outcomes. Mustar has made notable contributions to autonomous navigation, including exploring Intel’s Realsense T265 camera for visual odometry in omnidirectional mobile robots (2024), and developing an Edge AI-driven video analytics framework for victim detection in search-and-rescue robotics (2024), demonstrating his commitment to real-world impact. His earlier work includes designing an amphibious robot for culvert monitoring (2017) and a wireless tank robot navigation system controlled by hand gestures via an accelerometer sensor (2018). With over 18 total citations across his most-cited papers, Mustar’s research is steadily gaining recognition for its innovative integration of robotics, AI, and user-centered design, making him a promising voice in the field of interactive and autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Human-Robot Interaction Based GUI9 citations · 2017
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- 4Rancang Bangun Robot Amphibi Sebagai Sistem Monitoring Gorong-Gorong2 citations · 2017
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