Neural Network Model for Identifying Workspace, Forward and Inverse Kinematics of the 7-DOF YuMi 14000 ABB Collaborative Robot
| Autor: | R. Jill Urbanic, Morteza Alebooyeh |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Inverse kinematics Artificial neural network Computer science 020208 electrical & electronic engineering Control engineering 02 engineering and technology Kinematics Workspace Computer Science::Robotics 020901 industrial engineering & automation Control and Systems Engineering 0202 electrical engineering electronic engineering information engineering Robot Manipulator |
| Zdroj: | IFAC-PapersOnLine. 52:176-181 |
| ISSN: | 2405-8963 |
| DOI: | 10.1016/j.ifacol.2019.10.019 |
| Popis: | This research investigates development of a visual and analytical tool for the study of the seven degree of freedom (7-DOF) ABB 14000 YuMi robot. It provides an understanding of the manipulator workspace regions where they are visually represented for insight into the true work window. The developed tool is capable of realizing forward and inverse kinematics as well. The task is achieved using artificial neural networks that predict an inverse kinematic solution within an acceptable confidence interval (90th-95th percentile). Mathematical models, including all kinematic models i.e. the physical structure of manipulator joints and links, are developed and visually represented in the MATLAB platform by using the neural network toolbox. |
| Databáze: | OpenAIRE |
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