Dong-Sung Pae

Sangmyung University, Korea University

Papers

3

Total Citations

41

H-Index

3

About

Dong-Sung Pae specializes in autonomous driving, robotics, and intelligent control systems, with a focus on path planning and motion optimization. His major contribution lies in developing an obstacle-dependent Gaussian model predictive control framework for autonomous driving path planning, which enhances both safety and passenger comfort—a paper that has garnered 23 citations since 2021. He has also advanced robust visual tracking under challenging conditions, such as image blurring, by arbitrating between appearance- and feature-based detection methods (15 citations). Most recently, Pae has tackled the complex logistics problem of mixed palletizing, integrating practical reinforcement learning with configuration-space motion planning to handle real-time, variable-sized box packing—a notable achievement for industrial automation. His work bridges theoretical control methods with real-world robotic applications, demonstrating impact in both autonomous vehicle navigation and warehouse automation. With a growing citation record and contributions spanning from visual tracking to reinforcement learning-based manipulation, Pae is establishing himself as a versatile researcher in intelligent systems and robotics.

Research Focus

Key Achievements

3
H-Index
3
Papers
41
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Path Planning Based on Obstacle-Dependent Gaussian Model Predictive Control for Autonomous Driving
23 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Sangmyung University, Korea University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago