Manipulability Optimization of Redundant Manipulators Using Dynamic Neural Networks

By Long Jin, Shuai Li, Hung Manh La, Xin Luo. IEEE transactions on industrial electronics (1982. Print), 2017

336 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/8c55e4ee9b6d390c78cb88aab34117a161b0c720

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Zidong Wang

In Control and Systems Engineering

1. Qing-Long Han
2. Xiaohua Ge
3. Derui Ding
4. Zidong Wang
5. Xianming Zhang
6. Lei Ding
7. James Lam
8. Dong Yue

Citations in the corpus

• Accurate photovoltaic power forecasting models using deep LSTM-RNN (2017, background): “…used in various applications, such as optimal demand response in smart grids [54], control of single-phase converters [17], manipulator con-trol [27, 28, 30, 31], modeling crack growth of aluminum alloy [56], distributed task allocation of multiple robots [26], text recognition [43], and…”
• A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems (2019, background): “When the local communication among neighbor manipulators is taken into consideration, the addressed issue has to be enslaved to a set of auxiliary constraints only dependent on the neighbor information [83], [87], [88].”