Papers
1
Total Citations
33
H-Index
1
About
Yingjia Wan is a pioneering researcher at the intersection of assistive robotics and human-robot interaction, with a primary focus on developing autonomous navigation systems for visually impaired individuals. Her most impactful work, "Navigating Real-World Challenges: A Quadruped Robot Guiding System for Visually Impaired People in Diverse Environments" (2024), has already garnered 33 citations, signaling its rapid influence in the field. This study introduces a groundbreaking approach that leverages affordable quadruped robots—like robotic dogs—as intelligent guide systems, addressing critical limitations of traditional white canes and smart devices in complex, dynamic environments. Wan's major contribution lies in demonstrating how legged robots can autonomously navigate real-world obstacles, such as stairs, uneven terrain, and crowded spaces, while providing intuitive haptic feedback to users. By tackling practical challenges like sensor fusion, path planning, and user safety, her work bridges the gap between cutting-edge robotics and tangible accessibility solutions. This research not only advances the capabilities of quadruped platforms but also opens new avenues for inclusive technology design, making her a rising voice in robotics and disability studies. Her achievements highlight a commitment to translating theoretical robotics into life-changing applications.
Research Focus
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Top Papers
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