Name
Abstract | ||
|---|---|---|
The application scenarios of robots are becoming more and more complex, leading to higher and higher demand on skills for robots. This paper proposes a method to learn complex skill by decomposing it into basic skills, then train them respectively as well as combination into a whole, where reinforcement learning are used both in basic skill learning and in the integration. The method proposed is validated on the RoboCup small soccer robot platform via the skill of chasing and shooting ball and tested in both simulation environment and real world. It is verified our method has achieved a higher success rate comparing with traditional methods. Code is available here. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/RCAR52367.2021.9517586 | 2021 IEEE International Conference on Real-time Computing and Robotics (RCAR) |
Keywords | DocType | ISBN |
decision-making skill learning,soccer robot,reinforcement learning,basic skill learning,RoboCup small soccer robot platform | Conference | 978-1-6654-3679-3 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhike Chen | 1 | 0 | 0.34 |
| Zhiye He | 2 | 0 | 0.34 |
| Haozhe Du | 3 | 0 | 0.34 |
| Chengrui Han | 4 | 0 | 0.34 |
| Yunkai Wang | 5 | 0 | 0.34 |
| Zexi Chen | 6 | 0 | 3.72 |
| Rong Xiong | 7 | 11 | 5.61 |