Kleinmann, Karl ; Hormel, Michael ; Paetsch, Wolfgang (2023)
Intelligent Real-Time Control of a Multifingered Robot Gripper by Learning Incremental Actions.
In: IFAC Proceedings Volumes, 1992, 25 (10)
doi: 10.26083/tuprints-00023371
Article, Secondary publication, Publisher's Version
![[img]](https://tuprints.ulb.tu-darmstadt.de/style/images/fileicons/text.png) |
Text
1-s2.0-S1474667017508381-main.pdf Copyright Information: CC BY-NC-ND 4.0 International - Creative Commons, Attribution NonCommercial, NoDerivs. Download (1MB) |
| Item Type: | Article |
|---|---|
| Type of entry: | Secondary publication |
| Title: | Intelligent Real-Time Control of a Multifingered Robot Gripper by Learning Incremental Actions |
| Language: | English |
| Date: | 2023 |
| Place of Publication: | Darmstadt |
| Year of primary publication: | 1992 |
| Publisher: | IFAC - International Federation of Automatic Control |
| Journal or Publication Title: | IFAC Proceedings Volumes |
| Volume of the journal: | 25 |
| Issue Number: | 10 |
| DOI: | 10.26083/tuprints-00023371 |
| Corresponding Links: | |
| Origin: | Secondary publication service |
| Abstract: | Learning control systems are expected to have several advantages over conventional approaches when dealing with complex, high-dimensional processes. One example is the task of controlling grasping operations of a multifingered, multijoined robot gripper, which has been designed and implemented at our robotics lab (the Darmstadt-Hand). The Advanced Gripper Control with Learning Algorithms -AGRICOLA- presented in this paper is able to maintain a stable grasp even if disturbances are applied. Also it works for objects of different sizes for which the grasping has not been learned. Compared to the conventional stiffness approach the performance of the learning system is equal but the design is much easier, since less knowledge about the gripper-hardware has to be taken into account. The main part of the learning control loop is an associative memory storing the grasping behaviour as determined by the choice of an objective function. |
| Uncontrolled Keywords: | high-dimensional nonlinear process, stable grasp, object manipulation, associative memories, learning control loop |
| Status: | Publisher's Version |
| URN: | urn:nbn:de:tuda-tuprints-233712 |
| Additional Information: | Zugl. Konferenzveröffentlichung: IFAC Symposium on Artificial Intelligence in Real Time Control, 16.-18.06.1992, Delft, Netherlands |
| Classification DDC: | 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering |
| Divisions: | 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Intelligent Systems |
| Date Deposited: | 14 Mar 2023 10:49 |
| Last Modified: | 13 Jul 2023 14:36 |
| URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/23371 |
| PPN: | 50961941X |
| Export: |
 |
View Item |
Drucken
Impressum