Rio Prasetyo Lukodono
National Taiwan University of Science and Technology, University of Brawijaya
Papers
3
Total Citations
84
H-Index
3
About
Rio Prasetyo Lukodono is a leading researcher at the intersection of human–robot collaboration (HRC), sustainable manufacturing, and physiological computing. His work centers on making industrial robots not only more efficient but also safer and more responsive to human cognitive states. In his highly cited 2022 study, “Classification of mental workload in Human-robot collaboration using machine learning based on physiological feedback” (45 citations), Lukodono pioneered the use of real-time physiological signals—such as heart rate and skin conductance—to classify operators’ mental workload, enabling adaptive robot behavior that prevents overexertion. His 2021 paper, “Sustainable Human–Robot Collaboration Based on Human Intention Classification” (34 citations), further advanced the field by integrating intention prediction with sustainable manufacturing principles, demonstrating how smart HRC can reduce energy consumption while improving worker well-being. Most recently, his 2024 work on “Learning performance and physiological feedback-based evaluation for HRC” (5 citations) explores how machine learning can continuously assess and enhance collaborative learning between humans and robots. Lukodono’s contributions are shaping the next generation of human-centric, eco-friendly automation, making him a key voice in the drive toward Industry 5.0.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3