Publikationsdatenbank
Publication
Manipulating Deformable Linear Objects: Model-Based Adjustment-Motion for Vibration ReductionShigang Yue , Dominik Henrich
Abstract (english)
This paper addresses the problem of handling deformable linear objects (DLOs) in a suitable way to avoid acute vibration. An adjustment-motion that eliminates vibration of DLOs and can be attached to the end of any arbitrary end-effector's trajectory is presented, based on the concept of open-loop control. The presented adjustment-motion is a kind of agile end-effector motion with limited scope. To describe the dynamics of deformable linear objects, the finite element method is used to derive the dynamic differential equations. Genetic algorithm is used to find the optimal adjustment-motion for each simulation example. In contrast to previous approaches, the presented method can be treated as one of the manipulation skills and can be applied to different cases without major changes to the method.
Publication data
| Year: | 2001 |
| Publication date: | 12. June 2001 |
| Source: | The 10th International Conference on Advanced Robotics 2001, Aug. 22-25, Budapest, Hungary |
| Project: | RODEO |
| Referrer: | https://www.ai3.uni-bayreuth.de/de/publikationen/resypub/index.php?mode=pub_show&pub_ref=yue2001a |
BibTeX
@MISC{yue2001a,
TITLE = "Manipulating Deformable Linear Objects: Model-Based Adjustment-Motion for Vibration Reduction",
AUTHOR = "Yue, Shigang and Henrich, Dominik",
YEAR = "2001",
JOURNAL = "The 10th International Conference on Advanced Robotics 2001, Aug. 22-25, Budapest, Hungary",
HOWPUBLISHED = "\url{https://www.ai3.uni-bayreuth.de/de/publikationen/resypub/index.php?mode=pub_show&pub_ref=yue2001a}",
}
Download
| Filename | Size | Language | Format | ||||
|---|---|---|---|---|---|---|---|
| yue2001a.Manipulating.Deformable.Linear.Objects.ModelBased.A djustmentMotion.for.Vibration.Reduction.djvu |
159.5K | english | DJVU | download preprint | |||
| yue2001a.Manipulating.Deformable.Linear.Objects.ModelBased.A djustmentMotion.for.Vibration.Reduction.pdf |
392.3K | english | download preprint |