| id |
ecaade2017_252 |
| authors |
Sharif, Shani, Agrawal, Varun and Sweet, Larry |
| year |
2017 |
| title |
Adaptive Industrial Robot Control for Designers |
| source |
Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 151-158 |
| doi |
https://doi.org/10.52842/conf.ecaade.2017.2.151
|
| summary |
In this research, we present a system to allow designers to adaptively control an industrial robot from within a 3D modeling environment, for the purpose of real time feedback with respect to visual imagery of the object as well as robot pose during the fabrication process. Our work uses the Kuka industrial robots due to their capability in fabrication and programmability, and the Rhino 3D modeling software with the Grasshopper plugin which allows for visual programming for designers. A Microsoft Kinect sensor is used to provide visual feedback of the part during the fabrication process. We present the methodology used to develop the system, explaining various design and architecture choices made to allow for easy use of our system, while ensuring our system is open to further extension. We also show qualitative results of the fabrication process performed using our system in order to validate that our proposed system improves the interaction and collaboration between designer and robot when performing the task, in contrast to the iterative process that is generally followed. |
| keywords |
Human-robot collaboration; Robotic fabrication; Adaptive control; Feedback |
| series |
eCAADe |
| email |
|
| full text |
 file.pdf (4,972,133 bytes) |
| references |
Content-type: text/plain
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| last changed |
2022/06/07 07:56 |
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