Seungjun Woo

Sungkyunkwan University, Escuela Superior Politecnica del Litoral

Papers

Total Citations

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About

Seungjun Woo is a robotics researcher specializing in legged locomotion and autonomous navigation, with a particular focus on enabling quadruped robots to traverse complex, structured environments like stairways. His work addresses a critical challenge in field robotics: how to make legged robots reliably map and climb stairs using limited onboard sensing. Woo’s key contributions center on developing novel mapping and motion planning algorithms that allow quadrupeds to perceive stair geometry from close-range point-cloud data and execute stable, multi-step climbing behaviors. His most-cited paper, “Stair-mapping with Point-cloud Data and Stair-modeling for Quadruped Robot” (2019, 10 citations), introduces a method for reconstructing stair dimensions from sparse sensor measurements, while his subsequent work on plane-based stairway mapping (2020, 4 citations) improves robustness by estimating individual step planes. Woo has also analyzed motion strategies for climbing stairs in two or three steps and crossing obstacles, drawing inspiration from human gait efficiency. Though his citation counts are modest, his research is foundational for practical legged robot deployment in indoor environments, bridging the gap between perception and control for agile, real-world locomotion.