Yongguo Zhu

Papers

Total Citations

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About

Yongguo Zhu is a researcher specializing in robotics, autonomous navigation, and intelligent manufacturing, with a focus on optimizing algorithms for mobile robots and industrial automation. His most cited work, "Optimization Design and Experimental Study of Gmapping Algorithm" (2020, 16 citations), addresses critical challenges in simultaneous localization and mapping (SLAM) for indoor mobile robots. By enhancing the Rao-Blackwellized particle filter-based Gmapping algorithm, Zhu significantly reduces computational load and improves real-time performance—a key advancement for practical deployment in dynamic environments. More recently, his 2025 paper on "Robot trajectory planning for gear chamfer grinding" introduces a multi-objective collaborative optimization framework combined with quintic B-spline interpolation, achieving smoother and more precise trajectories for industrial grinding tasks. This work demonstrates his ability to bridge theoretical optimization with real-world manufacturing needs. Though early in his career, Zhu’s contributions to SLAM efficiency and robotic path planning have already garnered attention, laying a strong foundation for future innovations in autonomous systems and precision robotics.