Xiaosheng Zhu

Papers

Total Citations

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About

Xiaosheng Zhu is a researcher specializing in autonomous robotics, unmanned aerial vehicle (UAV) navigation, and intelligent path planning algorithms. His work centers on applying classical artificial intelligence techniques to solve complex real-world navigation challenges, particularly in environments populated by obstacles. Zhu's most recognized contributions focus on the adaptation and implementation of the A* algorithm for trajectory planning in UAVs and autonomous ground robots, demonstrating how grid-based computational models can efficiently identify optimal paths from origin to destination under constrained conditions. His 2014 paper on UAV trajectory planning using the A* algorithm stands as his most cited work, accumulating 5 citations, followed closely by his 2013 study on autonomous robot path planning with 4 citations. A complementary 2014 publication on collision-free path planning for aerial robots further reinforces his sustained commitment to this research domain. Collectively, these works address a critical intersection of artificial intelligence and robotics — autonomous navigation — which underpins technologies ranging from delivery drones to search-and-rescue systems. While Zhu's citation footprint remains emerging, his focused contributions provide foundational methodological insights valuable to students and practitioners entering the rapidly expanding field of autonomous aerial and ground vehicle systems.