Name
Abstract | ||
|---|---|---|
At present, cloud robots tend to be intelligent and cooperative. Based on this, we proposed a teaching method based on Imitation and a learning method that incorporates Incremental Learning and Meta Learning. We use Imitation Learning to teach robots, and more concretely, we propose a natural teaching method based on visual sense by using a depth camera, the robot can learn from the trajectory caught by the camera. Meta Learning helps robots understand the task and split it into some subtasks which enhances the level of generalization. Besides, once the circumstances change the robot can update the cloud database using Incremental Learning. Using proposed method, we make robots capable of learning and cooperating with other robots. It is no longer necessary for robots to learn based on a great number of data which is a shortcoming of traditional robots. The greatest advantage of this method is that we improve the learning efficiency of robots and enhance the level of generalization of the model. Our method was experimentally verified in a laboratory and the results indicated that the method improved the learning efficiency of robots. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ACCESS.2020.2966226 | IEEE ACCESS |
Keywords | DocType | Volume |
Imitation learning,cloud robot,incremental learning,meta learning | Journal | 8 |
ISSN | Citations | PageRank |
2169-3536 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guanglong Du | 1 | 0 | 2.37 |
| Zhiyao Wang | 2 | 0 | 0.34 |
| Zhelin Li | 3 | 0 | 0.34 |