Name
Abstract | ||
|---|---|---|
The Stewart platform's unique structure presents an interesting problem in its forward kinematics (FK) solution. It involves the solving of a series of simultaneous non-linear equations and, usually, non-unique, multiple sets of solutions are obtained from one set of data. In addition, most effort usually result in having to find the solution of a 16th-order polynomial by means of numerical methods. A simple feed-forward network was trained to recognise the relationship between the input values and the output values of the FK problem and was able to provide the solution around an average error of 1.0 ° and 1.0 mm. By performing a few iterations with an innovative offset adjustment, the performance of the trained network was improved tremendously. Two extra iterations with the offset adjustment reduced the average error of the same trained neural network to 0.017 ° and 0.017 mm. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1016/S0925-2312(97)00048-9 | Neurocomputing |
Keywords | Field | DocType |
Robot,Stewart platform,Parallel manipulator,Kinematics,Neural networks | Parallel manipulator,Kinematics,Polynomial,Computer science,Control theory,Forward kinematics,Artificial intelligence,Artificial neural network,Numerical analysis,Stewart platform,Machine learning,Offset (computer science) | Journal |
Volume | Issue | ISSN |
16 | 4 | 0925-2312 |
Citations | PageRank | References |
17 | 1.26 | 16 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Choon seng Yee | 1 | 17 | 1.26 |
| Kah-Bin Lim | 2 | 40 | 4.34 |