Trajectory Analysis of 6-DOF Industrial Robot Manipulators by Using Artificial Neural Networks.

Area of Science:

• Robotics and Automation
• Artificial Intelligence
• Control Systems

Background:

• Robot manipulators are crucial for industrial automation, offering speed, precision, and efficiency.
• Their complex, nonlinear nature necessitates optimized trajectory control for effective industrial application.
• Accurate positioning is vital for robot manipulators, especially in demanding sectors like the textile industry.

Purpose of the Study:

• To perform positioning analyses using artificial neural networks (ANNs) for robot manipulator systems in the textile industry.
• To improve and identify the optimal ANN model for achieving high-accuracy trajectory control and positioning.
• To evaluate the performance of different ANN learning algorithms for inverse kinematic analysis.

Main Methods:

• Applied artificial neural networks (ANNs) for positioning analyses of a 6-degree-of-freedom (DOF) industrial robot manipulator.
• Conducted inverse kinematic analyses using four learning algorithms: delta-bar-delta (DBD), online back propagation (OBP), quick back propagation (QBP), and random back propagation (RBP).
• Compared the performance of a 3-10-6 ANN structure with an improved 3-5-6 ANN structure, evaluating root mean square error (RMSE) and R-squared (R²) metrics.

Main Results:

• The QBP-based 3-10-6 type ANN structure demonstrated optimal performance for trajectory control estimation and modeling.
• The improved 3-5-6 ANN structure also showed promising results, with its performance metrics compared against the 3-10-6 structure.
• The study confirmed the effectiveness of the proposed neural predictors in accurately estimating and modeling robot manipulator trajectories.

Conclusions:

• The Quick Back Propagation (QBP) algorithm, within a 3-10-6 ANN structure, is highly effective for optimizing robot manipulator trajectory control.
• The developed neural network models are suitable for real-time industrial applications requiring precise robot manipulator trajectory analysis.
• This research contributes to enhancing the precision and efficiency of robotic systems in industrial automation.