39 citations · 85 across the 11 of their papers we have counts for
4 papers · 1 filter
ActionFlow: Equivariant, Accurate, and Efficient Policies with Spatially Symmetric Flow Matching
Niklas Funk, Julen Urain, Joao Carvalho +3
Spatial understanding is a critical aspect of most robotic tasks, particularly when generalization is important. Despite the impressive results of deep generative models in complex…
MoVEInt: Mixture of Variational Experts for Learning Human-Robot Interactions from Demonstrations
Vignesh Prasad, Alap Kshirsagar, Dorothea Koert +3
Shared dynamics models are important for capturing the complexity and variability inherent in Human-Robot Interaction (HRI). Therefore, learning such shared dynamics models can enh…
Transition State Clustering for Interaction Segmentation and Learning
Fabian Hahne, Vignesh Prasad, Alap Kshirsagar +4
Hidden Markov Models with an underlying Mixture of Gaussian structure have proven effective in learning Human-Robot Interactions from demonstrations for various interactive tasks v…
Kinematically Constrained Human-like Bimanual Robot-to-Human Handovers
Yasemin Göksu, Antonio De Almeida Correia, Vignesh Prasad +4
Bimanual handovers are crucial for transferring large, deformable or delicate objects. This paper proposes a framework for generating kinematically constrained human-like bimanual…