Liyang Zhang

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About

Liyang Zhang is a researcher specializing in intelligent robotics, autonomous navigation, and multi-sensor fusion, with a focus on advancing mobile robot localization and path planning. Their major contributions include developing novel optimization algorithms for robotic systems, most notably the application of a modified grey wolf optimizer (GWO) for patrol robot path planning, which addresses key limitations in traditional approaches such as slow convergence and local optima entrapment. This work, published in 2023, has already garnered 12 citations, reflecting its growing influence in the field. Additionally, Zhang has made significant strides in indoor mobile robot localization by integrating IMU, stereo camera, and LiDAR data with graph-based optimization techniques, achieving high accuracy and stability in sensor-asynchronous information fusion—a critical challenge for real-world deployment. This 2024 publication, with 7 citations, underscores their impact on multi-sensor fusion research. Zhang’s work is notable for its practical applicability, bridging theoretical optimization with real-time robotic performance, and is essential reading for students and researchers exploring intelligent navigation systems and autonomous robotics.