-
Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation
Versatile movement representations allow robots to learn new tasks and r...
01/29/2021 ∙ by Felix Frank, et al. ∙
0
∙
share
read it
-
Fast Approximate Geodesics for Deep Generative Models
The length of the geodesic between two data points along the Riemannian ...
12/19/2018 ∙ by Nutan Chen, et al. ∙
10
∙
share
read it
-
Active Learning based on Data Uncertainty and Model Sensitivity
Robots can rapidly acquire new skills from demonstrations. However, duri...
08/06/2018 ∙ by Nutan Chen, et al. ∙
8
∙
share
read it
