Shunya Kondo
Papers
1
Total Citations
8
H-Index
1
About
Shunya Kondo is a robotics researcher whose work centers on intelligent control systems for unmanned aerial vehicles (UAVs). His primary research areas include flight control, neural network-based adaptive control, and quad-rotor dynamics. Kondo’s most notable contribution is the development of a radial basis function neural network (RBFNN) integrated with PID control for quad-rotor flying robots, addressing the critical challenge of stable flight under external disturbances such as wind. This innovative approach allows control parameters to adapt in real time, significantly improving flight stability and robustness. His seminal 2017 paper on this topic has garnered 8 citations, reflecting its foundational role in adaptive UAV control research. Kondo’s work bridges the gap between classical control theory and modern machine learning, offering practical solutions for autonomous aerial systems. His contributions are particularly valuable for researchers and engineers developing resilient drones for applications in surveillance, delivery, and environmental monitoring. By enabling more reliable flight in unpredictable conditions, Kondo’s research continues to influence the evolution of intelligent robotics and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1