Jaemann Park
Papers
2
Total Citations
42
H-Index
2
About
Jaemann Park is a researcher specializing in intelligent control systems, fault-tolerant robotics, and heavy machinery automation. His work bridges advanced computational methods and practical mechatronic applications, with a focus on enhancing the safety and efficiency of autonomous vehicles and industrial equipment. Park’s most-cited paper, “Utilizing online learning based on echo-state networks for the control of a hydraulic excavator” (2014, 37 citations), introduces a novel approach to real-time adaptive control using reservoir computing, significantly improving precision in complex hydraulic systems. This contribution has influenced the development of more responsive and energy-efficient construction machinery. Additionally, his 2015 study on “Actuator reconfiguration control of a robotic vehicle with four independent wheel driving” (5 citations) presents a robust driving algorithm that maintains vehicle stability and closed-loop performance even after actuator failure, a critical advancement for autonomous ground vehicles operating in hazardous environments. Through these works, Park has demonstrated a commitment to creating resilient, learning-based control architectures that push the boundaries of both theoretical robotics and real-world automation.
Research Focus
Key Achievements
Top Papers
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