Zhiguo Tan

About

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Research Focus

Key Achievements

Top Papers

1. 1
   Repetitive motion of redundant robots planned by three kinds of recurrent neural networks and illustrated with a four-link planar manipulator’s straight-line example

   75 citations · 2009
2. 2
   New Varying-Parameter ZNN Models With Finite-Time Convergence and Noise Suppression for Time-Varying Matrix Moore–Penrose Inversion

   68 citations · 2019
3. 3
   Improved Gradient Neural Networks for Solving Moore–Penrose Inverse of Full-Rank Matrix

   39 citations · 2019
4. 4
   Robustness Analysis and Robotic Application of Combined Function Activated RNN for Time-Varying Matrix Pseudo Inversion

   31 citations · 2019
5. 5
   Noise-Tolerant and Finite-Time Convergent ZNN Models for Dynamic Matrix Moore–Penrose Inversion

   30 citations · 2019
6. 6
   A dual neural network applied to drift-free resolution of five-link planar robot arm

   19 citations · 2008
7. 7
   Improved recurrent neural networks for online solution of Moore‐Penrose inverse applied to redundant manipulator kinematic control

   18 citations · 2018
8. 8
   A Review of Deep Learning-Based LiDAR and Camera Extrinsic Calibration

   16 citations · 2024
9. 9
   A simplified LVI-based primal-dual neural network for repetitive motion planning of PA10 robot manipulator starting from different initial states

   14 citations · 2008
10. 10
    Self-motion planning of redundant robot manipulators based on quadratic program and shown via PA10 example

    11 citations · 2008

Key Collaborators