Xingyu Wang
Papers
1
Total Citations
4
H-Index
1
About
Xingyu Wang is an emerging researcher specializing in robotics, trajectory planning, and optimization algorithms, with a focus on practical industrial automation applications. Their most notable work addresses the challenge of efficient motion planning for freight train cleaning robots, demonstrating a sophisticated command of both mathematical modeling and metaheuristic optimization techniques. In this research, Wang employs seventh-degree polynomial interpolation combined with an improved Harris Hawks Optimization (HHO) algorithm to simultaneously minimize time and energy consumption in robotic trajectories — a dual-objective problem of significant practical importance in railway maintenance automation. Published in 2025, this work has already accumulated 4 citations, signaling early traction within the robotics and intelligent systems community. The research reflects a broader commitment to bridging theoretical optimization methods with real-world engineering constraints, particularly in heavy industrial environments where precision and efficiency are critical. For students and researchers working at the intersection of robotic motion planning, swarm intelligence, and industrial automation, Wang's contributions offer a compelling example of applied algorithmic innovation with direct relevance to smart manufacturing and infrastructure maintenance systems.
Research Focus
Key Achievements
Top Papers
- 1