23 citations · 33 across the 16 of their papers we have counts for
4 papers · 1 filter
Hierarchical Policy Blending as Inference for Reactive Robot Control
Kay Hansel, Julen Urain, Jan Peters +1
Motion generation in cluttered, dense, and dynamic environments is a central topic in robotics, rendered as a multi-objective decision-making problem. Current approaches trade-off…
SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion
Julen Urain, Niklas Funk, Jan Peters +1
Multi-objective optimization problems are ubiquitous in robotics, e.g., the optimization of a robot manipulation task requires a joint consideration of grasp pose configurations, c…
Learning Implicit Priors for Motion Optimization
Julen Urain, An T. Le, Alexander Lambert +3
In this paper, we focus on the problem of integrating Energy-based Models (EBM) as guiding priors for motion optimization. EBMs are a set of neural networks that can represent expr…
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…