88 citations · 407 across the 41 of their papers we have counts for
5 papers · 1 filter
A New Data Source for Inverse Dynamics Learning
Daniel Kappler, Franziska Meier, Nathan Ratliff +1
Modern robotics is gravitating toward increasingly collaborative human robot interaction. Tools such as acceleration policies can naturally support the realization of reactive, ada…
SE3-Pose-Nets: Structured Deep Dynamics Models for Visuomotor Planning and Control
Arunkumar Byravan, Felix Leeb, Franziska Meier +1
In this work, we present an approach to deep visuomotor control using structured deep dynamics models. Our deep dynamics model, a variant of SE3-Nets, learns a low-dimensional pose…
Learning Sensor Feedback Models from Demonstrations via Phase-Modulated Neural Networks
Giovanni Sutanto, Zhe Su, Stefan Schaal +1
In order to robustly execute a task under environmental uncertainty, a robot needs to be able to reactively adapt to changes arising in its environment. The environment changes are…
Online Learning of a Memory for Learning Rates
Franziska Meier, Daniel Kappler, Stefan Schaal
The promise of learning to learn for robotics rests on the hope that by extracting some information about the learning process itself we can speed up subsequent similar learning ta…
Real-time Perception meets Reactive Motion Generation
Daniel Kappler, Franziska Meier, Jan Issac +7
We address the challenging problem of robotic grasping and manipulation in the presence of uncertainty. This uncertainty is due to noisy sensing, inaccurate models and hard-to-pred…