Yingjie Zhang
Papers
2
Total Citations
113
H-Index
2
About
Yingjie Zhang is a researcher specializing in mobile robotics, autonomous navigation, and computer vision, with a particular focus on path planning and object detection. Their most impactful contribution is in mobile robot path planning, where they developed an improved localized particle swarm optimization algorithm that addresses long-standing challenges in the field, such as local minima, premature convergence, and low efficiency. This work, published in 2020, has garnered 110 citations, reflecting its significance in advancing robot automation technology. Zhang has also explored deep learning-based object detection, proposing a method that integrates deep learning with B-spline level sets to achieve accurate object recognition and three-dimensional positioning in color images. While this 2022 work is earlier in its citation trajectory, it demonstrates Zhang’s versatility in combining classical optimization techniques with modern deep learning approaches. Their research bridges theoretical algorithm development with practical robotic applications, contributing to more efficient and reliable autonomous systems. Zhang’s work is particularly relevant for researchers and students working on intelligent robotics, autonomous navigation, and computer vision.
Research Focus
Key Achievements
Top Papers
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