- Tytuł:
- Efficient learning variable impedance control for industrial robots
- Autorzy:
-
Li, C.
Zhang, Z.
Xia, G.
Xie, X.
Zhu, Q. - Powiązania:
- https://bibliotekanauki.pl/articles/200716.pdf
- Data publikacji:
- 2019
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
variable impedance control
reinforcement learning
efficient
Gaussian process
industrial robots
impedancja
poprawa efektywności
wydajność
model Gaussa
roboty przemysłowe - Opis:
- Compared with the robots, humans can learn to perform various contact tasks in unstructured environments by modulating arm impedance characteristics. In this article, we consider endowing this compliant ability to the industrial robots to effectively learn to perform repetitive force-sensitive tasks. Current learning impedance control methods usually suffer from inefficiency. This paper establishes an efficient variable impedance control method. To improve the learning efficiency, we employ the probabilistic Gaussian process model as the transition dynamics of the system for internal simulation, permitting long-term inference and planning in a Bayesian manner. Then, the optimal impedance regulation strategy is searched using a model-based reinforcement learning algorithm. The effectiveness and efficiency of the proposed method are verified through force control tasks using a 6-DoFs Reinovo industrial manipulator.
- Źródło:
-
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 2; 201-212
0239-7528 - Pojawia się w:
- Bulletin of the Polish Academy of Sciences. Technical Sciences
- Dostawca treści:
- Biblioteka Nauki
Artykuł