Name
Abstract | ||
|---|---|---|
Accurate manipulation of a deformable body such as a piece of fabric is difficult because of its many degrees of freedom and unobservable properties affecting its dynamics. To alleviate these challenges, we propose the application of feedback-based control to robotic fabric strip folding. The feedback is computed from the low dimensional state extracted from a camera image. We trained the controller using reinforcement learning in simulation which was calibrated to cover the real fabric strip behaviors. The proposed feedback-based folding was experimentally compared to two state-of-the-art folding methods and our method outperformed both of them in terms of accuracy. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/IROS40897.2019.8967657 | 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
Keywords | Field | DocType |
feedback-based fabric strip folding,accurate manipulation,deformable body,unobservable properties,feedback-based control,robotic fabric strip folding,low dimensional state,feedback-based folding,camera image,degrees of freedom | Computer vision,Control theory,Simulation,Artificial intelligence,Engineering,Camera image,Unobservable,Reinforcement learning | Journal |
Volume | ISSN | ISBN |
abs/1904.01298 | 2153-0858 | 978-1-7281-4005-6 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vladimír Petrík | 1 | 22 | 3.69 |
| V. Kyrki | 2 | 652 | 61.79 |