The Training Set Automating for a Neural Network Model of an Industrial Robot Control System
Vyacheslav I. Voronov, Victor A. Smolnikov, Л. И. Воронова, Olga L. Antonycheva, Nikita V. Belov
- 发表年份
- 2024
- 引用次数
- 4
摘要
The industrial robot control system solves a large number of tasks that affect the ease of integration and efficiency of the manipulator in the technological process. One of its main tasks is to calculate in real time the trajectory of the manipulator flange movement taking into account the selected type of movement. In particular, this task can be solved using a neural network model. The article describes the solution of the problem of automating the creation of a training set for a neural network model that forms the trajectory of movement of an industrial manipulator. The source of data for the set is a KUKA KR4 R600 manipulator and its digital twin created in the “Rational Production” software. The training set includes many sets of the manipulator joint angle vectors (generalised coordinates) that uniquely define the current position of the robot and its flange in space.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002