Junjie Liu

Jiangsu University of Science and Technology, Aberystwyth University

Papers

Total Citations

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About

Junjie Liu is a researcher whose work spans computer vision and robotics, with particular focus on trajectory optimization and feature detection methodologies. Liu's most notable contribution lies in the domain of automated spray painting systems, where a 2019 study introduced an innovative approach to optimizing spray trajectories across three-dimensional entities. By employing surface modeling techniques based on flat patch adjacency graphs (FPAG) and developing finite range models tailored to complex 3D geometries, this work addressed a significant challenge in industrial automation — achieving uniform coating coverage with computational efficiency. The paper has garnered 22 citations, reflecting its practical relevance to manufacturing and robotic automation communities. Complementing this applied robotics work, Liu's earlier research from 2009 contributed to the foundational computer vision literature through a rigorous comparative analysis of corner detection methods. With 16 citations, this study evaluated state-of-the-art interest point detection techniques across applications including camera calibration, robot localization, and object tracking — areas critical to intelligent systems development. Together, these contributions demonstrate Liu's consistent engagement with bridging theoretical computer vision principles and real-world robotic applications, offering tools and methodologies that support the advancement of autonomous and semi-autonomous industrial systems.