Andrianto Handojo

Papers

Total Citations

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About

Andrianto Handojo’s research bridges the gap between traditional Indonesian culture and modern robotics, with a focus on human-robot interaction and gesture recognition. His most-cited work, “Musical gesture recognition for interactive angklung robot” (2013, 7 citations), introduces a novel approach to controlling a robotic angklung—a traditional Indonesian bamboo instrument—using the same hand signs a conductor would use to lead human players. This contribution not only advances gesture-based control systems but also preserves and reimagines cultural heritage through technology. Handojo’s research demonstrates how robotics can enhance interactive musical experiences, making traditional performances more accessible and engaging. His work is particularly notable for its interdisciplinary nature, combining computer vision, machine learning, and ethnomusicology. By creating a system that interprets human gestures in real time, Handojo has laid groundwork for more intuitive human-robot collaboration in artistic settings. His achievements highlight the potential of culturally inspired robotics to inspire new forms of creative expression and education, offering a compelling example of how technology can honor tradition while pushing the boundaries of innovation.