Sung Su Kim

About

Sung Su Kim is a leading researcher in intelligent control systems and autonomous robotics, with a particular focus on real-time hardware implementation and visual perception. His most influential work, "Hardware Implementation of a Real-Time Neural Network Controller With a DSP and an FPGA for Nonlinear Systems" (2007, 245 citations), represents a landmark contribution to the field. In this paper, Kim pioneered the integration of field programmable gate arrays (FPGAs) with digital signal processing (DSP) boards to create intelligent control hardware capable of solving complex nonlinear system control problems in real time. This work has been widely recognized for bridging the gap between theoretical neural network controllers and practical, deployable hardware solutions. Kim has also contributed to autonomous navigation, developing a method for visual recognition of structural corridor landmarks—such as T-junctions and L-junctions—using vanishing point detection and hidden Markov models (2010). This research enhances a robot’s ability to understand its spatial environment, a critical capability for indoor autonomous navigation. Kim’s work continues to influence the development of intelligent, real-time control systems and robotic perception technologies.

Research Focus

Key Achievements

Top Papers

1. 1
   Hardware Implementation of a Real-Time Neural Network Controller With a DSP and an FPGA for Nonlinear Systems

   245 citations · 2007
2. 2
   Visual Recognition of Types of Structural Corridor Landmarks Using Vanishing Points Detection and Hidden Markov Models

   4 citations · 2010

Key Collaborators

Contact & Links