Papers
3
Total Citations
58
H-Index
3
About
Chang-Soo Park is a versatile researcher whose work spans robotics, indoor positioning systems, and autonomous perception — fields that sit at the intersection of intelligent systems and real-world engineering applications. Among his most recognized contributions is a novel indoor location awareness method that leverages LED-based visible light communication, using received signal strength ratios and time division multiplexing to enable precise localization for autonomous robot vehicles — work that has garnered 30 citations and demonstrates his talent for practical, hardware-grounded innovation. Park has also made meaningful strides in bipedal robotics, proposing an evolutionary-optimized central pattern generator that produces stable, modifiable walking gaits by generating naturalistic foot and pelvis trajectories — a contribution cited 25 times that reflects deep expertise in bio-inspired control systems. More recently, his research has turned toward deep learning and autonomous driving, with a semi-supervised domain adaptation framework for 3D object detection designed to address sensor variability across real-world environments. Taken together, Park's portfolio reveals a researcher consistently motivated by bridging theoretical advances with deployable solutions, making meaningful contributions to robotics, localization, and intelligent sensing systems that matter to engineers and practitioners alike.
Research Focus
Key Achievements
Top Papers
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