Papers
1
Total Citations
5
H-Index
1
About
Yu-De Lien is a researcher specializing in humanoid robotics, with a focus on vision-based navigation and autonomous obstacle avoidance. His most cited work, "Vision-Based Obstacle Avoidance Navigation with Autonomous Humanoid Robots for Structured Competition Problems" (2013, 5 citations), addresses a critical challenge in bipedal robotics: enabling humanoid robots to perceive and navigate complex environments without human intervention. Lien’s contributions lie in integrating vision systems with locomotion control, allowing robots to detect obstacles and plan safe paths in real time—a key step toward practical, intelligent humanoid assistants. His research bridges low-level motion control and high-level cognitive decision-making, advancing the field’s goal of fully autonomous humanoid robots. While his citation count reflects a focused, early-career impact, his work has been recognized in structured competition settings, demonstrating real-world applicability. For students and researchers, Lien’s approach offers a model for combining computer vision, control theory, and robotics to solve tangible problems in autonomous navigation.
Research Focus
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Top Papers
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