Sung-Hyeon Joo

About

Sung-Hyeon Joo is a leading researcher in autonomous robotics, specializing in semantic environment modeling, knowledge representation, and cognitive navigation. His work bridges the gap between human-like understanding and robotic task execution, with a focus on enabling robots to process semantic knowledge for efficient assistance in domestic, hospital, and industrial settings. Joo’s most impactful contribution is his ontology-based framework for knowledge representation in robotic systems, which has garnered 54 citations and is foundational for integrating social roles into autonomous agents. He also developed a neuro-inspired cognitive navigation framework (41 citations) that mimics human environment modeling and planning, addressing long-standing challenges in robotic cognition. His practical innovations include an edge deployment system for real-time face mask recognition using deep learning (24 citations) and an automatic elevator button localization method for multi-story navigation (21 citations). Joo’s work has been widely recognized for advancing autonomous navigation in dynamic environments, with over 190 total citations across his top papers. His research continues to shape the future of intelligent robotics, particularly in human-robot interaction and multi-robot task planning.

Research Focus

Key Achievements

Top Papers

1. 1
   Ontology-Based Knowledge Representation in Robotic Systems: A Survey Oriented toward Applications

   54 citations · 2021
2. 2
   Autonomous Navigation Framework for Intelligent Robots Based on a Semantic Environment Modeling

   41 citations · 2020
3. 3
   Edge Deployment Framework of GuardBot for Optimized Face Mask Recognition With Real-Time Inference Using Deep Learning

   24 citations · 2022
4. 4
   Automatic Elevator Button Localization Using a Combined Detecting and Tracking Framework for Multi-Story Navigation

   21 citations · 2020
5. 5
   Comparison of Object Recognition Approaches using Traditional Machine Vision and Modern Deep Learning Techniques for Mobile Robot

   14 citations · 2019
6. 6
   3D Recognition Based on Sensor Modalities for Robotic Systems: A Survey

   12 citations · 2021
7. 7
   A Flexible Semantic Ontological Model Framework and Its Application to Robotic Navigation in Large Dynamic Environments

   10 citations · 2022
8. 8
   A Realtime Autonomous Robot Navigation Framework for Human like High-level Interaction and Task Planning in Global Dynamic Environment

   7 citations · 2019
9. 9
   Semantic Knowledge-Based Hierarchical Planning Approach for Multi-Robot Systems

   5 citations · 2023
10. 10
    A robust SLAM algorithm using hybrid map approach

    5 citations · 2018

Key Collaborators

Contact & Links