Xu Zhu
Papers
1
Total Citations
1
H-Index
1
About
Xu Zhu is a robotics researcher whose work centers on multi-robot systems, path planning, and obstacle avoidance in complex environments. Their most-cited paper, "A Multi-Robot Planning Algorithm with Quad Tree Map Division for Obstacles of Irregular Shape" (2022), introduces a novel approach that combines quad tree-based map decomposition with an optimal shortest-path algorithm to enhance coordination among multiple automated guided vehicles (AGVs). By integrating a waiting mode and motion coordination strategy, Zhu’s algorithm significantly improves efficiency in simulated global maps with irregular obstacles—a critical challenge for warehouse logistics and industrial automation. While this work has garnered 1 citation, it reflects a focused contribution to scalable multi-robot scheduling. Zhu’s research addresses the practical need for robust, real-time navigation in cluttered settings, offering a foundation for future studies in decentralized robot teams. Their work stands out for its innovative fusion of spatial partitioning and collision-avoidance logic, making it a valuable reference for researchers tackling multi-agent path planning in non-ideal environments.
Research Focus
Key Achievements
Top Papers
- 1