Menusha Munasinghe
Papers
2
Total Citations
10
H-Index
2
About
Menusha Munasinghe’s research lies at the intersection of human-robot interaction, augmented reality, and intelligent automation, with a focus on making robots more responsive and intuitive for collaborative tasks. In her foundational work, she designed an interactive robotic head with human-like movements, aiming to bridge the gap between mechanical construction and natural social behavior in robotics. This paper, cited 7 times, laid early groundwork for more expressive and approachable robotic systems. Building on this, Munasinghe advanced the field by integrating deep learning with augmented reality to enable a team of robots to learn from human demonstrations and automate complex tasks. Her 2020 paper, with 3 citations, explores how AR-based human interactions can train multi-robot systems, pushing toward more adaptive and autonomous teamwork. Her contributions are particularly notable for combining practical interface design with machine learning, offering a pathway toward robots that not only follow commands but learn from human guidance. Munasinghe’s work is a valuable resource for students and researchers interested in socially aware robotics, human-robot collaboration, and the future of intuitive automation.
Research Focus
Key Achievements
Top Papers
- 1Design of an interactive robotic head with human-like movements7 citations · 2013
- 2