Papers
3
Total Citations
13
H-Index
2
About
Yujin Heo is a robotics researcher whose work centers on advancing humanoid robot autonomy, with a particular focus on perception, control, and motion generation for wheeled humanoid platforms. His major contributions lie in bridging the gap between high-level perception and low-level real-time control, enabling robots to execute complex tasks in dynamic environments. Heo’s most cited paper, “Motion Generation Interface of ROS to PODO Software Framework for Wheeled Humanoid Robot” (2019, 6 citations), introduces a critical software architecture that integrates non-real-time robot operating systems with real-time control frameworks, a foundational step for intelligent manipulation and navigation. His subsequent work, “Dynamic Humanoid Locomotion Over Rough Terrain With Streamlined Perception-Control Pipeline” (2021, 5 citations), tackles the challenge of vision-aided bipedal locomotion, addressing uncertainties from rapid motion and foot-contact forces that can destabilize visual-inertial systems. Heo also contributed to “Fast Perception, Planning, and Execution for a Robotic Butler: Wheeled Humanoid M-Hubo” (2019, 2 citations), which demonstrates practical service robot applications for aging populations. Through these efforts, Heo has established himself as a key figure in developing robust, integrated pipelines for humanoid robots, with his work cited for its impact on real-world robotic deployment and autonomy.
Research Focus
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