Reinforcement Learning

Robot Navigation & Control

SAMPLE TEXT. We apply reinforcement learning to locomotion and navigation, with emphasis on safety, sample efficiency, and transfer from simulation to hardware.

Team

Gon-Woo Kim

Professor

Department of Intelligent Systems and Robotics

SLAM & State Estimation · Autonomous Navigation · Vision-Language-Action (VLA) · Reinforcement Learning

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Seon-Woo Kim

M.S. Student

Reinforcement Learning

Tien Dat Nguyen

M.S. Student

Reinforcement Learning

Publications

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2026

1 paper

Memory-based Deep Reinforcement Learning on Topological Sub-goal Generation for Mobile Robot Navigation Under Unknown Environment

Tien Dat Nguyen, Phan Thanh Danh, and Gon-Woo Kim

ICCAS 2026 — International Conference on Control, Automation and Systems

2025

1 paper

Perception and Deep Reinforcement Learning-Based Local Path Planner for Autonomous Vehicles

Phan Thanh Danh and Gon-Woo Kim

JKROS 2025 — Journal of Korea Robotics Society

DOI

2024

2 papers

Cooperative deep reinforcement learning policies for autonomous navigation in complex environments

Tran Van Manh and Gon-Woo Kim

IEEE Access 2024 — IEEE Access

Cited by 7

DOI

Mapless Navigation with Distributional Reinforcement Learning

Tran Van Manh and Gon-Woo Kim

JKROS 2024 — Journal of Korea Robotics Society

Cited by 4

DOI

2023

2 papers

Refined State: Sim-To-Real Transfer Deep Reinforcement Learning for Mobile Robots in Complex Environments

Tran Van Manh and Gon-Woo Kim

UR 2023 — International Conference on Ubiquitous Robots

Sim-to-Real Transfer for Mapless Navigation

Tran Van Manh and Gon-Woo Kim

KRoC 2023 — Korea Robotics Society Annual Conference

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