Weijie Yang

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About

Weijie Yang is a researcher whose work sits at the intersection of intelligent robotics, autonomous navigation, and 3D spatial reconstruction. His primary research areas include path planning algorithms, 3D reconstruction for construction robotics, and sensor integration for mobile platforms. Yang’s most impactful contribution is his improved A* path planning method for grid maps, which directly addresses the critical limitations of excessive turning points and slow search speeds in traditional A* algorithms. This work, published in 2022 and already garnering 75 citations, demonstrates a practical solution for mobile robots equipped with LiDAR and inertial measurement units, significantly enhancing obstacle avoidance efficiency in real-world environments. Additionally, Yang has explored 3D reconstruction for specialized applications, developing an improved marching cube (MC) algorithm for shotcreting robots. By integrating point cloud splicing and normal reorientation with explosion-proof LiDAR data, his method enables accurate 3D arch surface reconstruction during tunnel spraying operations. While this work is more recent with 4 citations, it highlights Yang’s ability to solve domain-specific engineering challenges. His research is particularly valuable for students and engineers working on autonomous systems, construction robotics, and real-time spatial mapping.