Kosei Noda
Papers
2
Total Citations
16
H-Index
2
About
Kosei Noda is a researcher in human-robot interaction and collaborative control systems, with a focus on semi-autonomous robotic swarms and variable autonomy architectures. His work addresses the critical challenge of balancing human cognitive load with robotic autonomy, particularly in dynamic environments such as agricultural applications. Noda’s 2019 paper, “On Passivity-Shortage of Human Operators for A Class of Semi-autonomous Robotic Swarms” (10 citations), introduces a passivity-short-based framework that ensures stable human-enabled motion synchronization while analyzing operator workload. Building on this, his 2020 paper “Human-Robot Collaboration with Variable Autonomy via Gaussian Process” (6 citations) presents a novel control architecture using Gaussian Process regression to dynamically adjust autonomy levels, enhancing collaboration in tasks like robotic manipulation. Though early in his career, Noda’s contributions are notable for integrating passivity theory with machine learning to create adaptive, safe human-robot systems. His work has implications for agricultural robotics and semi-autonomous swarms, offering a principled approach to managing human-robot team performance. As his citation impact grows, Noda is establishing himself as a thoughtful contributor to the future of collaborative robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Human-Robot Collaboration with Variable Autonomy via Gaussian Process6 citations · 2020