Hyansu Bae

Yeungnam University, Korea Electrotechnology Research Institute

Papers

Total Citations

209

H-Index

About

Hyansu Bae is a leading researcher in autonomous multi-robot systems and intelligent navigation, with a focus on reinforcement learning and sensor fusion. Their most influential work, "Multi-Robot Path Planning Method Using Reinforcement Learning" (2019, 189 citations), introduces a novel algorithm that combines Deep Q-learning with Convolutional Neural Networks, enabling robots to navigate complex environments without requiring pre-designed formations or exhaustive area searches—a significant advancement over conventional path planning methods. Bae further demonstrated practical innovation in "Path Planning of a Sweeping Robot Based on Path Estimation of a Curling Stone Using Sensor Fusion" (2020, 15 citations), where they developed a specialized multi-robot system for Olympic curling, optimizing ice-sweeping trajectories to enhance stone motion. Additionally, their work on "Image Distortion and Rectification Calibration Algorithms and Validation Technique for a Stereo Camera" (2021, 5 citations) addresses critical calibration challenges for stereo cameras in smart vehicles and mobile robots, improving obstacle detection reliability. With a cumulative citation impact exceeding 200, Bae’s contributions bridge theoretical reinforcement learning with real-world robotic applications, from industrial automation to sports technology, establishing them as a key innovator in autonomous systems and sensor-based navigation.