Xiangyu Zou
Papers
2
Total Citations
33
H-Index
2
About
Xiangyu Zou is a leading researcher in intelligent autonomous systems, with a primary focus on pedestrian trajectory prediction for edge agents such as socially-aware robots and autonomous vehicles. His work addresses a critical challenge in human-robot interaction: enabling machines to safely and accurately navigate crowded, dynamic environments. Zou’s major contributions lie in developing advanced spatial-temporal graph-based models that capture complex pedestrian interactions and multimodal movement patterns. His influential 2020 paper, “Multi-Modal Pedestrian Trajectory Prediction for Edge Agents Based on Spatial-Temporal Graph,” has garnered 24 citations, establishing a foundational framework for safety navigation in interactive scenes. He further refined this approach in his 2022 work, “Multimodal Pedestrian Trajectory Prediction Based on Relative Interactive Spatial-Temporal Graph,” which tackles the inherent randomness of pedestrian motion by modeling both past movements and inter-pedestrian interactions. Through these innovations, Zou has significantly advanced the reliability of autonomous navigation systems, making them more responsive to unpredictable human behavior. His research is essential reading for engineers and scientists developing the next generation of safe, socially-aware autonomous vehicles and mobile robots.
Research Focus
Key Achievements
Top Papers
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