Robot manipulators are considered as the key element in flexible manufacturing systems. Nonetheless, for a successful accomplishment of robot integration, the robots need to be accurate. The leading source of inaccuracy is the mismatch
between the prediction made by the robot controller and the actual system. This work presents techniques for identification of actual kinematic parameters and pose accuracy compensation using a laser-based 3-D measurement system. In identification stage, both direct search and gradient methods are utilized. A computer simulation of the identification is performed using virtual position measurements. Moreover, experimentation is performed on industrial robot FANUC Robot R-2000iB/210F to test full pose and relative position accuracy improvements.
In addition, accuracy obtained by classical parametric methodology is improved by the implementation of artificial neural networks. Neuro-parametric method proves an enhanced improvement in simulation results. The whole proposed theory is reflected by developed simulation software throughout this work while achieving accuracy nine times better when comparing before and after implementation.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12614819/index.pdf |
| Date | 01 September 2012 |
| Creators | Bayram, Alican |
| Contributors | Konukseven, Ilhan |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | Access forbidden for 1 year |
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