Bo‐Yeong Kang
Papers
19
Total Citations
247
H-Index
8
About
Dr. Bo‐Yeong Kang is a leading researcher in intelligent robotics, with a focus on autonomous navigation, multi-robot coordination, and human-robot interaction. Her most significant contributions lie in coverage path planning for cleaning robots, where she developed a scalable map decomposition method that enables efficient operation in large environments like airports and libraries—a paper that has garnered 76 citations. She also advanced robot path planning with a fast genetic algorithm (27 citations) and a PBIL-based approach (14 citations), both designed to minimize path distance and computational time. In multi-robot systems, Kang introduced a cleaning distribution method based on map decomposition (26 citations) and explored cooperative table-balancing using Q-learning and deep reinforcement learning. Her work extends into agricultural robotics, where she applied deep learning to detect early-stage pests like fall armyworms (20 citations), and into social robotics, with studies on child-robot aesthetic interaction and continuous emotion estimation from facial expressions (18 citations). Notably, her research on adaptive sentiment feedback for deep reinforcement learning in cooperative robots (19 citations) bridges emotion and autonomy. With over 200 total citations, Kang’s interdisciplinary work continues to shape practical, intelligent robotic systems for real-world challenges.
Research Focus
Key Achievements
Top Papers
- 1
- 2Fast genetic algorithm for robot path planning27 citations · 2013
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- 7ROBIL: Robot Path Planning Based on PBIL Algorithm14 citations · 2014
- 8Cooperative Robot for Table Balancing Using Q-learning8 citations · 2020
- 9Exploiting Child-Robot Aesthetic Interaction for a Social Robot7 citations · 2012
- 10Table-Balancing Cooperative Robot Based on Deep Reinforcement Learning6 citations · 2023