Xinglan Zhang

Chongqing University of Technology, Beijing University of Technology

Papers

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About

Xinglan Zhang is a robotics researcher whose work bridges path planning, 3D reconstruction, and bio-inspired micro-robotics. Their most impactful contribution is an improved A* path planning algorithm for grid maps, which addresses the critical limitations of excessive turning points and slow search speeds in traditional A* methods. This work, published in 2022, has already garnered 75 citations, reflecting its practical significance for mobile robot navigation using lidar and inertial measurement systems. Zhang also advanced construction robotics by developing an improved marching cube (MC) algorithm for 3D reconstruction of tunnel arch surfaces, enabling shotcreting robots to operate more effectively. Earlier in their career, Zhang explored bio-inspired design with a tortoise-like flexible micro-robot using ICPF actuators, capable of crawling and swimming—a foundational study in micro-robotics with 2 citations. This diverse portfolio demonstrates Zhang’s ability to solve real-world engineering challenges, from optimizing autonomous navigation to enabling precise construction automation, making their work relevant for students and researchers in robotics, autonomous systems, and intelligent control.