39 citations · 85 across the 11 of their papers we have counts for
13 papers
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…
Learning Multimodal Latent Dynamics for Human-Robot Interaction
Vignesh Prasad, Lea Heitlinger, Dorothea Koert +3
This article presents a method for learning well-coordinated Human-Robot Interaction (HRI) from Human-Human Interactions (HHI). We devise a hybrid approach using Hidden Markov Mode…
MILD: Multimodal Interactive Latent Dynamics for Learning Human-Robot Interaction
Vignesh Prasad, Dorothea Koert, Ruth Stock-Homburg +2
Modeling interaction dynamics to generate robot trajectories that enable a robot to adapt and react to a human's actions and intentions is critical for efficient and effective coll…
Learning Human-like Hand Reaching for Human-Robot Handshaking
Vignesh Prasad, Ruth Stock-Homburg, Jan Peters
One of the first and foremost non-verbal interactions that humans perform is a handshake. It has an impact on first impressions as touch can convey complex emotions. This makes han…
Human-Robot Handshaking: A Review
Vignesh Prasad, Ruth Stock-Homburg, Jan Peters
For some years now, the use of social, anthropomorphic robots in various situations has been on the rise. These are robots developed to interact with humans and are equipped with c…
Advances in Human-Robot Handshaking
Vignesh Prasad, Ruth Stock-Homburg, Jan Peters
The use of social, anthropomorphic robots to support humans in various industries has been on the rise. During Human-Robot Interaction (HRI), physically interactive non-verbal beha…
Variational Clustering: Leveraging Variational Autoencoders for Image Clustering
Vignesh Prasad, Dipanjan Das, Brojeshwar Bhowmick
Recent advances in deep learning have shown their ability to learn strong feature representations for images. The task of image clustering naturally requires good feature represent…
Evaluation of the Handshake Turing Test for anthropomorphic Robots
Ruth Stock-Homburg, Jan Peters, Katharina Schneider +2
Handshakes are fundamental and common greeting and parting gestures among humans. They are important in shaping first impressions as people tend to associate character traits with…
Epipolar Geometry based Learning of Multi-view Depth and Ego-Motion from Monocular Sequences
Vignesh Prasad, Dipanjan Das, Brojeshwar Bhowmick
Deep approaches to predict monocular depth and ego-motion have grown in recent years due to their ability to produce dense depth from monocular images. The main idea behind them is…
SfMLearner++: Learning Monocular Depth & Ego-Motion using Meaningful Geometric Constraints
Vignesh Prasad, Brojeshwar Bhowmick
Most geometric approaches to monocular Visual Odometry (VO) provide robust pose estimates, but sparse or semi-dense depth estimates. Off late, deep methods have shown good performa…