Learning parametric dynamic movement primitives from multiple demonstrations

@article{Matsubara2011LearningPD,
  title={Learning parametric dynamic movement primitives from multiple demonstrations},
  author={Takamitsu Matsubara and Sang-Ho Hyon and Jun Morimoto},
  journal={Neural networks : the official journal of the International Neural Network Society},
  year={2011},
  volume={24 5},
  pages={493-500}
}
Learning from demonstration has shown to be a suitable approach for learning control policies (CPs). However, most previous studies learn CPs from a single demonstration, which results in limited scalability and insufficient generalization toward a wide range of applications in real environments. This paper proposes a novel approach to learn highly scalable CPs of basis movement skills from multiple demonstrations. In contrast to conventional studies with a single demonstration, i.e., dynamic… CONTINUE READING
Highly Cited
This paper has 106 citations. REVIEW CITATIONS

From This Paper

Topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 52 extracted citations

Motion planning with movement primitives for cooperative aerial transportation in obstacle environment

2017 IEEE International Conference on Robotics and Automation (ICRA) • 2017
View 4 Excerpts
Highly Influenced

Learning compact parameterized skills with a single regression

2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids) • 2013
View 5 Excerpts
Highly Influenced

Exploiting the task space redundancy in robot programming by demonstration

2018 IEEE International Conference on Mechatronics and Automation (ICMA) • 2018

106 Citations

0102030'12'14'16'18
Citations per Year
Semantic Scholar estimates that this publication has 106 citations based on the available data.

See our FAQ for additional information.

Similar Papers

Loading similar papers…