Name
Title | ||
|---|---|---|
A digital twin-based sim-to-real transfer for deep reinforcement learning-enabled industrial robot grasping |
Abstract | ||
|---|---|---|
•A digital twin-enabled approach for achieving effective transfer of DRL algorithms to a physical robot is proposed.•A digital twin system of the physical robotic system is established, which is used to correct the real grasping point.•Experimental results verify the effectiveness of the intelligent grasping algorithm and the digital twin-enabled sim-to-real transfer approach and mechanism. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.rcim.2022.102365 | Robotics and Computer-Integrated Manufacturing |
Keywords | DocType | Volume |
Deep reinforcement learning,Sim-to-real transfer,Digital twin,Robot grasping | Journal | 78 |
ISSN | Citations | PageRank |
0736-5845 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yongkui Liu | 1 | 0 | 0.68 |
| He Xu | 2 | 0 | 0.34 |
| Ding Liu | 3 | 611 | 32.97 |
| Lihui Wang | 4 | 0 | 1.69 |