Xueyu Zhang
Papers
2
Total Citations
4
H-Index
1
About
Xueyu Zhang is a leading researcher in intelligent robotics and sensor-based hazard assessment, with a particular focus on the safety and stability of magnetic adhesion wall-climbing robots. Their work addresses critical challenges in high-altitude robotic operations, where the risk of overturning poses significant dangers. Zhang’s major contributions include developing advanced classification models that integrate Improved CNN-LSTM architectures with accelerometer sensor data, achieving robust detection of hazardous states. This work, published in 2025 and garnering 3 citations, demonstrates a novel approach to real-time risk evaluation. Additionally, Zhang pioneered a dynamic feature selection method using reinforcement learning—specifically Proximal Policy Optimization (PPO)—to enhance the reliability of hazard state classification in these robots, a study that has already attracted 1 citation. By combining deep learning with reinforcement learning, Zhang has advanced the field of autonomous robotic safety, enabling more resilient and intelligent systems for industrial applications. Their research not only improves the operational stability of climbing robots but also sets a foundation for future innovations in adaptive sensor-driven hazard mitigation.
Research Focus
Key Achievements
Top Papers
- 1
- 2