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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Neto, P. Pires, J.N. Moreira, A.P. |
| Copyright Year | 2009 |
| Description | Author affiliation: Institute for Systems and Robotics (ISR) - Department of Electrical and Computer Engineering of the University of Porto, Rua Dr. Roberto Frias, 4200-465, Portugal (Moreira, A.P.) || Industrial Robotics Laboratory - Mechanical Engineering Department of the University of Coimbra, POLOII, Pinhal de Marrocos, 3030-788, Portugal (Neto, P.; Pires, J.N.) |
| Abstract | Most of industrial robots are still programmed using the typical teaching process, through the use of the robot teach pendant. In this paper is proposed an accelerometer-based system to control an industrial robot using two low-cost and small 3-axis wireless accelerometers. These accelerometers are attached to the human arms, capturing its behavior (gestures and postures). An Artificial Neural Network (ANN) trained with a back-propagation algorithm was used to recognize arm gestures and postures, which then will be used as input in the control of the robot. The aim is that the robot starts the movement almost at the same time as the user starts to perform a gesture or posture (low response time). The results show that the system allows the control of an industrial robot in an intuitive way. However, the achieved recognition rate of gestures and postures (92%) should be improved in future, keeping the compromise with the system response time (160 milliseconds). Finally, the results of some tests performed with an industrial robot are presented and discussed. |
| Starting Page | 1192 |
| Ending Page | 1197 |
| File Size | 495528 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424450817 |
| ISSN | 19449445 |
| DOI | 10.1109/ROMAN.2009.5326285 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-09-27 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Industrial control Service robots Electrical equipment industry Defense industry Educational robots Robot control Control systems Accelerometers Artificial neural networks Delay |
| Content Type | Text |
| Resource Type | Article |
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