Lingyu Guo
Papers
1
Total Citations
2
H-Index
1
About
Dr. Lingyu Guo is a pioneering researcher in human-robot interaction, with a specialized focus on close-proximity front-following systems that enable more intuitive and responsive collaboration. Their key research areas include multimodal sensor fusion, depth-temporal attention mechanisms, and walking intention prediction for robotic systems. Dr. Guo’s most notable contribution is the development of a novel depth-temporal attention model that integrates dual modality data—combining visual and depth information—to predict human walking intentions in real-time. This work, published in 2025 and already garnering 2 citations, addresses a critical gap in traditional robot following methods, which typically require maintaining significant distance and limit interaction quality. By enabling robots to operate in close proximity to humans, Dr. Guo’s research enhances the immediacy and naturalness of human-robot collaboration, with potential applications in assistive robotics, manufacturing, and service industries. Their innovative approach to attention-based temporal modeling represents a significant advancement in making robotic systems more adaptive and context-aware, promising to transform how robots and humans work together in shared spaces.
Research Focus
Key Achievements
Top Papers
- 1