1 citations · 1 across the 3 of their papers we have counts for
5 papers
A Hierarchical Approach to Active Pose Estimation
Jascha Hellwig, Mark Baierl, Joao Carvalho +2
Creating mobile robots which are able to find and manipulate objects in large environments is an active topic of research. These robots not only need to be capable of searching for…
Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning
Julen Urain, Anqi Li, Puze Liu +2
Reactive motion generation problems are usually solved by computing actions as a sum of policies. However, these policies are independent of each other and thus, they can have conf…
Structured Policy Representation: Imposing Stability in arbitrarily conditioned dynamic systems
Julen Urain, Davide Tateo, Tianyu Ren +1
We present a new family of deep neural network-based dynamic systems. The presented dynamics are globally stable and can be conditioned with an arbitrary context state. We show how…
ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows
Julen Urain, Michelle Ginesi, Davide Tateo +1
We introduce ImitationFlow, a novel Deep generative model that allows learning complex globally stable, stochastic, nonlinear dynamics. Our approach extends the Normalizing Flows f…
Generalized Multiple Correlation Coefficient as a Similarity Measurements between Trajectories
Julen Urain, Jan Peters
Similarity distance measure between two trajectories is an essential tool to understand patterns in motion, for example, in Human-Robot Interaction or Imitation Learning. The probl…