Papers
1
Total Citations
9
H-Index
1
About
Yaoyi He is a researcher whose work lies at the critical intersection of autonomous navigation and human behavior modeling, with a primary focus on pedestrian trajectory prediction. His most cited work, "Multimodal Pedestrian Trajectory Prediction Based on Relative Interactive Spatial-Temporal Graph" (2022), addresses one of the most challenging problems in robotics and autonomous driving: anticipating the inherently random and multimodal nature of pedestrian movement. He’s key contribution is the development of a novel framework that captures the complex, relative spatial-temporal interactions between individuals in a crowd, moving beyond simple linear predictions to model the diverse, socially-aware paths pedestrians might take. This research, which has garnered early citations, is foundational for enabling autonomous vehicles and mobile robots to navigate safely and efficiently in dense, unpredictable human environments. By tackling the core challenge of understanding human intention from motion cues, Yaoyi He is helping to bridge the gap between machine perception and real-world social dynamics, making significant strides toward safer human-robot interaction.
Research Focus
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Top Papers
- 1