Zhenyu Meng

Papers

Total Citations

H-Index

About

Zhenyu Meng is a researcher whose work centers on path planning and graph-based search algorithms, with a particular focus on improving efficiency in robotic and autonomous vehicle navigation. His most cited paper, "An Improved JPS Algorithm in Symmetric Graph" (2015, 9 citations), addresses a fundamental challenge in path planning: optimizing the Jump Point Search (JPS) algorithm for symmetric grid graphs. This work contributes to reducing computational overhead in classical route-searching problems, which are critical for applications in robotics, unmanned aerial vehicles (UAVs), and vehicle navigation. By refining how algorithms handle symmetric environments, Meng’s research helps enable faster and more reliable pathfinding in real-world systems. While his citation count reflects a focused and emerging impact, his contributions are notable for targeting a specific, practical bottleneck in graph-based search—a key area in AI and robotics. His work underscores the importance of algorithmic efficiency in autonomous systems, offering insights that can benefit both students and researchers exploring path planning, graph theory, or mobile robotics.