Name
Title | ||
|---|---|---|
Robot Learning System Based on Adaptive Neural Control and Dynamic Movement Primitives. |
Abstract | ||
|---|---|---|
This paper proposes an enhanced robot skill learning system considering both motion generation and trajectory tracking. During robot learning demonstrations, dynamic movement primitives (DMPs) are used to model robotic motion. Each DMP consists of a set of dynamic systems that enhances the stability of the generated motion toward the goal. A Gaussian mixture model and Gaussian mixture regression a... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TNNLS.2018.2852711 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | Field | DocType |
Trajectory,Robot learning,Dynamics,Feature extraction,Acceleration,Stability analysis | Robot learning,Computer vision,Control theory,Pattern recognition,Computer science,Feature extraction,Artificial intelligence,Acceleration,Robot,Trajectory,Mixture model,Dynamical system | Journal |
Volume | Issue | ISSN |
30 | 3 | 2162-237X |
Citations | PageRank | References |
18 | 0.57 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chenguang Yang | 1 | 2213 | 138.71 |
| Chuize Chen | 2 | 28 | 1.73 |
| Wei He | 3 | 806 | 22.67 |
| Rongxin Cui | 4 | 330 | 14.59 |
| Zhijun Li | 5 | 1051 | 56.61 |