Research Fields

Optimal Control and Game Theory Applications

Mean-field game theory summary

Control multiple agents in a decentralized manner through mean-field game theory, utilizing the pre-computed optimal strategy g*

Two-wheeled unmanned vehicle differential game results

[Distributed Optimal Control of Two-Wheeled Unmanned Vehicles: Differential Game Approach]

Developed and applied mean-field differential game theory for distributed non-cooperative optimal control of partially observed large-scale two-wheeled unmanned vehicles

Leader follower operation experiments
Hexarotor stackelberg game results

[Distributed Optimal Control of Hexarotor: Stackelberg Game Approach]

Applied partially observed mean-field Stackelberg game theory for leader-follower distributed optimal flight control of large-scale hexarotor groups

Hexarotor trajectory and error convergence

Reinforcement Learning and Machine Learning Theory and Applications

SACHER algorithm and UAV path planning results

[Reinforcement Learning-Based SACHER Algorithm for UAV Path Planning and Collision Avoidance]

Active management and load shedding control results

[Reinforcement Learning-Based Active Management of Power Systems and Emergency Load Shedding Control]

Multi objective RL and maximum norm minimization

[Single-Policy-Based Multi-Objective Reinforcement Learning: Maximum Norm Minimization Method for Expanding the Pareto Front]

Autonomous Driving and Intelligent Robot Control

Robot platforms

Research and Implementation of Intelligent Control Algorithms Based on Various Robot Platforms

ERP-42 driving experiments and simulation

Development and Validation of Autonomous Driving Algorithms for ERP-42 Vehicle Using Various Sensor Fusion Technologies