Papers
1
Total Citations
4
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About
Ruojin An is a researcher focused on advancing autonomous systems through improved human-robot interaction and environmental perception. Their primary research areas include pedestrian trajectory prediction, generative adversarial networks (GANs), and scene-constrained modeling for intelligent mobile robots and unmanned driving. An’s most notable contribution is the development of a pedestrian trajectory prediction method that integrates scene constraints into generative adversarial networks, addressing a critical limitation of the standard SGAN (social generative adversarial networks) model, which lacks comprehensive environmental understanding. This work, published in 2024 and garnering 4 citations, enhances the ability of autonomous systems to anticipate pedestrian movements by incorporating contextual scene information, thereby improving safety and reliability in dynamic environments. An’s research directly tackles challenges in perceptual interaction between robots and their surroundings, marking a significant step toward more robust autonomous navigation. Their work is particularly relevant for students and researchers in robotics, computer vision, and intelligent transportation systems, offering a practical approach to bridging the gap between social interaction modeling and environmental constraints in trajectory forecasting.
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Top Papers
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