Papers
3
Total Citations
31
H-Index
3
About
Qiaoyu Xu is a researcher at the forefront of intelligent robotic manipulation, with a primary focus on enhancing the precision and autonomy of large-scale hydraulic robotic arms. His work masterfully bridges classical control theory with modern artificial intelligence, tackling fundamental challenges in industrial robotics. Xu’s major contributions center on developing novel hybrid algorithms that combine optimization techniques with neural networks to solve critical problems. Notably, his 2024 paper on positioning error compensation introduced an Improved Secretary Bird Optimization Algorithm (ISBOA) to train a BP neural network, achieving significant error reduction in rock drilling manipulators. In parallel, he addressed the persistent local minimum issue in artificial potential fields by integrating deep reinforcement learning, creating a more robust active collision avoidance system. His third key contribution involves an adaptive spider wasp optimization (ASWO) algorithm for inverse kinematics, directly improving the end positioning accuracy of large hydraulic arms under real-world constraints like gravity and material deformation. With each of his most-cited papers accumulating over 10 citations within a single year, Xu’s work is rapidly gaining recognition for its practical impact on industrial automation, offering scalable solutions that enhance both the safety and precision of heavy machinery in demanding environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3