Papers
38
Total Citations
2,038
H-Index
23
About
Sung Jin Yoo is a prominent control systems researcher whose work sits at the intersection of nonlinear control theory, robotics, and neural network-based adaptive systems. His research has made substantial contributions to the trajectory tracking and formation control of nonholonomic wheeled mobile robots, flexible-joint robotic systems, and networked multi-robot systems. Yoo's most celebrated contributions include pioneering adaptive neural sliding mode control methods for mobile robots operating under model uncertainties and external disturbances, garnering over 285 citations, and a widely adopted simplified adaptive control framework for electrically driven nonholonomic robots accounting for actuator dynamics, cited over 230 times. His innovative integration of self-recurrent wavelet neural networks with dynamic surface control and generalized predictive control techniques further advanced robust adaptive control for complex robotic systems. Beyond single-robot control, Yoo has made significant strides in multi-robot coordination, addressing real-world challenges including unknown slippage, skidding, connectivity preservation, collision avoidance, and fault tolerance in networked formations. His 2015 work on distributed formation tracking under slippage effects has accumulated over 130 citations, reflecting its broad influence. Collectively, his research portfolio represents a rigorous and practically impactful body of work essential reading for researchers tackling modern autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
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- 9Adaptive formation control in absence of leader's velocity information69 citations · 2010
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