Article ID: | iaor20014016 |
Country: | Netherlands |
Volume: | 38 |
Issue: | 4 |
Start Page Number: | 467 |
End Page Number: | 478 |
Publication Date: | Dec 2000 |
Journal: | Computers & Industrial Engineering |
Authors: | Popplewell Neil, Balakrishnan Subramaniam, Thomlinson M. |
Keywords: | neural networks |
It is normal when programming a robotic manipulator to provide the end effector's orientation and position at the pick up and drop off locations. Additional sensory information and intelligence is needed, however, to detect the presence of a part as well as its location if the assembly site cannot be controlled precisely by employing expensive jigs or fixtures. This paper investigates, for this purpose, the application of solely an inexpensive laser sensor mounted unobtrusively to the end effector of a CRS robot having customized hardware and open software. Data from the sensor is converted into a single ‘Feature Value Vector’ to recognize a part and accurately determine its location by using a neural network and back propagation training. The procedure's viability is tested by assembling a set of tightly meshing gears under poor ambient lighting.