Papers
1
Total Citations
4
H-Index
1
About
Haoyang Yuan’s research lies at the intersection of computer vision, sensor fusion, and robotics, with a focus on enabling intelligent systems to perceive and navigate their environments more effectively. His most-cited work, “A Novel Object Detection and Localization Approach via Combining Vision with Lidar Sensor” (2021), tackles a critical challenge in autonomous robotics: the loss of global visual object information during movement. Yuan proposed an innovative two-component vision-based scheme that integrates a lightweight convolutional neural network (CNN) for efficient object detection with lidar data for precise spatial localization. This hybrid approach enhances both accuracy and robustness in dynamic settings, offering a practical solution for real-time robotic perception. With 4 citations, this paper has already drawn attention for its potential applications in autonomous driving and mobile robotics. Yuan’s contributions demonstrate a keen ability to bridge theoretical advances with engineering challenges, making his work valuable for researchers developing sensor-aware systems. His ongoing efforts continue to push the boundaries of how machines understand and interact with the physical world.
Research Focus
Key Achievements
Top Papers
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