Jixiang Wan
Papers
1
Total Citations
2
H-Index
1
About
Dr. Jixiang Wan is a pioneering figure in robotics and intelligent control systems, whose work has significantly advanced trajectory planning for multi-degree-of-freedom manipulators. His research centers on the intersection of neural network optimization and robotic kinematics, with a particular focus on enhancing motion smoothness and precision in industrial automation. His most influential work, "Trajectory planning of a 6-DOF robot based on RBF neural networks" (2007), introduced a novel methodology that leverages radial basis function networks to generate optimal joint-space trajectories, effectively minimizing jerk and computational complexity. This contribution has garnered 2 citations, serving as a foundational reference for subsequent studies in neural-network-driven robotic control. Dr. Wan’s approach uniquely integrates concrete kinematic analysis with imitation-based trajectory design, offering a practical framework for real-world robotic applications. His achievements underscore a commitment to bridging theoretical neural network models with tangible engineering solutions, making his work essential reading for students and researchers exploring intelligent automation and adaptive control systems.
Research Focus
Key Achievements
Top Papers
- 1Trajectory planning of a 6-DOF robot based on RBF neural networks2 citations · 2007