Research

Smart Mobility (Autonomous Vehicles, Intelligent Trasportation, etc.)

Autonomous Vehicles (Trajectory Planning and Tracking Control)

Safe driving is a core technology in autonomous vehicles. We focus on trajectory planning and tracking control algorithms to optimize vehicle behavior. These algorithms are designed with considerations for ride comfort, safety, and cost, contributing to the advancement of autonomous driving systems and the realization of smart mobility.

Autonomous Mobile Robot (AMR)

Autonomous mobile robots require integrated perception, decision-making, planning, and control to operate reliably in factories, warehouses, and other dynamic environments. We develop explainable, robust, and optimal autonomy solutions that enable AMRs to understand their surroundings, make transparent decisions, and maintain safe and efficient operation under uncertainty and changing conditions.

Intelligent Transportation

With technological advancements, research on smart mobility beyond traditional transportation is essential. We study intelligent transportation systems to create more convenient, safe, and sustainable mobility solutions.

Optimal Control (Advanced Control, System Modeling, Sensor-fusion Estimation, etc.)

Advanced Control (Low-cost & High Performance & Robustness)

At SMOC Lab, we research advanced control theories that are applicable not only to mobility but also to various industrial fields. We focus on low-cost sensor-based control, high-precision control performance, and robust control systems, contributing to advancements across multiple industries.

System Modeling

We research modeling techniques for new systems, including control-oriented modeling, to enable mathematical and physical analysis. Our work not only contributes to academia but also serves as the foundation for developing innovative control strategies and functionalities.

Sensor-fusion Estimation

Due to cost and hardware limitations, certain states or parameters in systems cannot be directly measured. We design estimation algorithms using mathematical techniques and learning-based approaches to infer such information. Additionally, we research sensor fusion and system fusion algorithms to address the needs of intelligent systems.

Defense Mobility Systems (Adaptive and Robust Control)

Defense Ground Vehicles

Reliable operation of defense ground vehicles requires consistent performance under payload variations, component degradation, and harsh terrain conditions. We focus on real-time load estimation and adaptive and robust control for multi-axle electric drive systems, including self-propelled artillery and other heavy-duty military vehicles.

Electrified Defense Mobility

Electrified defense mobility systems must maintain traction and stability on low-friction and uneven terrain. We develop wheel-slip estimation and traction control algorithms for electric armored vehicles and unmanned ground vehicles to suppress excessive slip and improve mobility under varying road and load conditions.

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