Yanfu Zhang
Papers
2
Total Citations
10
H-Index
2
About
Yanfu Zhang is a researcher specializing in autonomous systems, robotics, and machine learning, with a focus on motion prediction and visual perception for dynamic environments. His work addresses critical challenges in enabling intelligent agents to operate safely and effectively alongside moving actors, such as people or vehicles. Zhang’s major contributions include developing a semi-supervised regression approach to improve heading direction estimation for aerial filming, which enhances the generalization of models trained on limited data. He also pioneered a deep inverse reinforcement learning framework that integrates kinematics and environmental context to predict off-road vehicle trajectories, a key capability for autonomous navigation and tracking in unstructured settings. Both of his most-cited papers have garnered 5 citations each, reflecting their foundational role in advancing motion prediction from a third-person perspective. By combining visual input with contextual reasoning, Zhang’s research bridges the gap between perception and planning, enabling robots to anticipate agent behavior and execute more intelligent, adaptive actions. His work is particularly relevant for applications in autonomous drones, off-road robotics, and human-robot interaction, where accurate motion forecasting is essential for safety and performance.
Research Focus
Key Achievements
Top Papers
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- 2