Hyeongwoo Kang

Pukyong National University, Sogang University

Papers

Total Citations

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About

Hyeongwoo Kang is a researcher whose work bridges environmental monitoring and robotics, with a focus on satellite-based aerosol classification and tensegrity robot locomotion. In environmental science, Kang developed a random forest model to classify aerosol types over Asian capital cities using satellite data from 2018–2020, integrating Aerosol Robotic Network (AERONET) observations to improve accuracy. This work, cited 19 times, provides critical insights into regional air pollution sources and transport. In robotics, Kang co-authored "Spikebot: A Multigait Tensegrity Robot with Linearly Extending Struts" (2023, 15 citations), which introduced a novel tensegrity robot capable of multiple gaits through linearly extending struts—addressing key limitations in speed and locomotion diversity for these resilient, packable structures. By advancing both atmospheric remote sensing and bio-inspired robotics, Kang demonstrates versatility in tackling complex, interdisciplinary challenges. Their contributions are particularly valuable for students and researchers interested in machine learning applications for environmental monitoring or innovative approaches to soft robotics and locomotion.