Zhenye Sun

Papers

Total Citations

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About

Zhenye Sun is a robotics researcher whose work centers on enhancing the perceptual and navigational capabilities of autonomous systems, particularly service and mobile robots operating in indoor environments. His primary research areas include visual semantic navigation, 3D environmental mapping, and human-robot interaction. Sun’s most significant contribution is a deep learning-based, three-layer perception framework for visual semantic navigation, which leverages transfer learning to improve a robot’s ability to recognize places, rotation regions, and “sides” during navigation. This work, published in 2018, has garnered 31 citations, marking it as his most influential paper to date. He has also developed a robust relocalization algorithm that allows robots to re-establish their position within a pre-built 3D map when starting from an unknown viewpoint, addressing a critical challenge in persistent autonomy. Additionally, Sun has explored intuitive human-robot interaction, designing a gesture-based navigation system that enables non-expert users—including the elderly and children—to guide a robot through unknown environments for 3D mapping. By combining deep learning, multi-dimensional mapping, and accessible control interfaces, Sun’s research directly advances the real-world deployment of intelligent, user-friendly robots.