Kinematic Control of Redundant Manipulators Using Neural Networks

@article{Li2017KinematicCO,
  title={Kinematic Control of Redundant Manipulators Using Neural Networks},
  author={Shuai Cheng Li and Yunong Zhang and Long Jin},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2017},
  volume={28},
  pages={2243-2254}
}
Redundancy resolution is a critical problem in the control of robotic manipulators. Recurrent neural networks (RNNs), as inherently parallel processing models for time-sequence processing, are potentially applicable for the motion control of manipulators. However, the development of neural models for high-accuracy and real-time control is a challenging problem. This paper identifies two limitations of the existing RNN solutions for manipulator control, i.e., position error accumulation and the… CONTINUE READING