Danchi Jiang
Papers
2
Total Citations
112
H-Index
2
About
Danchi Jiang is a leading researcher in robotics and neural network control systems, with a focus on the kinematic control of redundant robot manipulators. His most influential work, the 1999 paper “A Lagrangian network for kinematic control of redundant robot manipulators,” has garnered over 104 citations, introducing a recurrent neural network that solves inverse kinematics problems in real time through quadratic optimization. This contribution laid the groundwork for efficient redundancy resolution in robotic systems, enabling smoother and more adaptive motion control. Jiang further advanced the field with his 2002 study on a two-layer recurrent neural network, which enhanced kinematic control by employing bidirectionally connected neuron arrays to process end-effector velocity signals. His research bridges theoretical optimization and practical robotics, offering scalable solutions for complex manipulation tasks. Jiang’s work is widely recognized for its impact on autonomous systems and industrial robotics, making him a key figure in the development of intelligent control architectures. His contributions continue to inform modern approaches to robotic motion planning and neural-based control.
Research Focus
Key Achievements
Top Papers
- 1A Lagrangian network for kinematic control of redundant robot manipulators104 citations · 1999
- 2