Jinsuk Choi
Papers
4
Total Citations
35
H-Index
3
About
Jinsuk Choi is a leading researcher in advanced robotics control, specializing in adaptive and intelligent control systems for robot manipulators. His work bridges model-free control, reinforcement learning, and robust estimation to achieve high-precision motion in complex environments. Choi’s most impactful contribution is the **Adaptive Model-Free Control with Nonsingular Terminal Sliding-Mode (AMC-NTSM)** (2020, 23 citations), which cancels nonlinearities and uncertainties using delayed measurements, enabling superior tracking accuracy. He further advanced the field with a **Reinforcement Learning-based Adaptive Time-Delay Control (RL-TDC)** (2022, 6 citations), offering more intelligent and aggressive control than traditional methods. His research also addresses real-world challenges, such as a robust control scheme for mobile manipulators on uneven terrain using IMU-based motion compensation (2022, 4 citations), and improving RL robustness via uncertainty and disturbance estimators (2022, 2 citations). By integrating learning-based approaches with classical control theory, Choi’s work pushes the boundaries of autonomous manipulation, making robots more reliable and adaptive in unstructured environments.
Research Focus
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Top Papers
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