Yingjun Lv

Shandong University of Science and Technology

Papers

Total Citations

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About

Yingjun Lv’s research centers on intelligent sensing and autonomous navigation, with a particular focus on path recognition systems for mobile platforms. Their most-cited work, “Application Analysis of the Linear CCD in the Path Recognition System” (2007), addresses critical limitations of traditional photoelectric sensors—namely, insufficient information capture, poor anti-interference capability, and limited forward-looking range. By proposing the use of Linear CCD technology, Lv demonstrated how to enhance the reliability and foresight of raceway recognition, a foundational contribution to the development of vision-guided vehicles. This early work, cited 4 times, laid the groundwork for subsequent advances in sensor fusion and real-time image processing. Lv’s research has implications for autonomous robotics, intelligent transportation, and industrial automation, where robust environmental perception is essential. Their ability to identify and solve practical sensor limitations reflects a career dedicated to bridging theoretical optics with applied engineering. For students and researchers exploring low-cost, high-performance sensing solutions, Lv’s work offers a clear example of how incremental sensor innovation can drive broader system-level improvements in autonomous navigation.