AMR Navigation
Safe crosswalk navigation for autonomous mobile robots operating around signalized urban intersections.
M.S. Student · KAIST Mobility
Autonomous Mobile Robot Navigation for Intelligent Intersections
I am Myeonghyeon Kim, a master's student at KAIST working on autonomous mobile robot navigation in urban intersection environments. My research focuses on SPaT/R2X-assisted crosswalk navigation, ROS 2-based robotic systems, LiDAR-based navigation, and infrastructure-aware intersection intelligence.
SPaT/R2X
Communication-assisted decision making using signal phase and remaining-time information from infrastructure.
Intersection Intelligence
Infrastructure-aware perception and scene understanding for pedestrians, vehicles, traffic lights, and occlusions.
Current Work
Recent Research Progress
Recent work centers on turning crosswalk navigation into a deployable robotic system: from real-world R2X/SPaT experiments to simulation-based validation and LiDAR-driven autonomous navigation.
SPaT/R2X AMR Crosswalk Navigation
Developed a time-aware AMR crossing framework using SPaT remaining-time information and a Time-to-Cross decision rule.
Delivery Robot ROS 2 Integration
Built a Delivery Robot simulation and integration pipeline with LiDAR, IMU, camera, odometry, joint states, and ROS 2 topics.
Fast-LIO2 and Nav2 Pipeline
Configured LiDAR-based SLAM and navigation components to support map generation, localization, and autonomous driving tests.
Isaac Sim and VLM Scenarios
Extending intersection scenarios in simulation for infrastructure-camera and VLM-based scene understanding research.
Selected Projects
Representative Research Projects
SPaT-Assisted AMR Crosswalk Navigation
A ROS 2-based framework integrating Nav2, SPaT/R2X messages, and a hybrid safety node for signal-aware AMR crossing.
LiDAR-based Robot Navigation with Fast-LIO2 and Nav2
Integration of LiDAR SLAM, mapping, localization, and Nav2-based navigation for mobile robot operation.
Isaac Sim-based Delivery Robot Digital Twin
Simulation environment for Delivery Robot sensing, ROS 2 communication, LiDAR/IMU/camera configuration, and scenario validation.
Publications
Selected Publications & Posters
Time-Aware Crosswalk Navigation for Autonomous Mobile Robots Using SPaT-Based R2X Communication
Myeonghyeon Kim, Junyoung Kim, Inhi Kim. IEEE ITSC 2026 Late-Breaking Results Poster, accepted.
R2X-Based Robust Navigation System for Autonomous Mobile Robots in Urban Intersections
Myeonghyeon Kim, Junyoung Kim, Inhi Kim, Gyounghun Chun. Korean ITS Spring Conference Poster, 2026.
Multi-Camera Pedestrian Full Trajectory Perception Using YOLO, DeepSORT, and Homography Transform
Myeonghyeon Kim, Inhi Kim. ITS Asia-Pacific 2025 submission.
CV
Curriculum Vitae
Education
- KAIST, M.S. Student, Cho Chun Shik Graduate School of Mobility
- Kookmin University, Automotive IT Convergence background
Technical Skills
- Robotics: ROS 2, Nav2, SLAM, LiDAR-camera systems, mobile robot navigation
- Simulation: Isaac Sim, digital twin environments, scenario generation
- Programming: Python, C++, MATLAB, LaTeX
- Perception/AI: YOLO, DeepSORT, Homography Transform, VLMs, sensor fusion, traffic signal recognition
Contact
Get in Touch
I am interested in autonomous mobile robots, intelligent transportation systems, communication-assisted navigation, and infrastructure-based scene understanding.