Xiaohua Ye
Papers
1
Total Citations
7
H-Index
1
About
Xiaohua Ye is a researcher whose work centers on the intersection of robotics, artificial intelligence, and advanced optimization algorithms. Their most notable contribution lies in the development of intelligent control systems for heavy machinery, specifically through the inverse calculation of laser-guided demolition robots. Ye pioneered a novel approach that combines gravitational search algorithms with differential evolution neural networks to create a global nonlinear mapping model—translating laser measuring points into precise joint cylinder strokes. This work, published in 2020 and garnering 7 citations, addresses the fundamental challenge of balancing population diversity with convergence speed in neural network optimization, a critical bottleneck in real-time robotic control. By enabling more accurate and efficient inverse kinematics for demolition robots, Ye's research has practical implications for construction automation and hazardous environment operations. Their methodology demonstrates how hybrid metaheuristic algorithms can enhance the performance of artificial neural networks in complex engineering applications, marking a significant step forward in the field of intelligent robotic systems and computational intelligence.
Research Focus
Key Achievements
Top Papers
- 1