15 citations · 35 across the 12 of their papers we have counts for
12 papers
Semantic-Geometric Task Representations for Bimanual Manipulation from Human Demonstrations to Robot Action Planning
Franziska Herbert, Vignesh Prasad, Han Liu +2
Learning structured task representations from human demonstrations is essential for bimanual manipulation, where action ordering, object involvement, and interaction geometry vary…
Investigating the Effect of LED Signals and Emotional Displays in Human-Robot Shared Workspaces
Maria Ibrahim, Alap Kshirsagar, Dorothea Koert +1
Effective communication is essential for safety and efficiency in human-robot collaboration, particularly in shared workspaces. This paper investigates the impact of nonverbal comm…
Grasp Diffusion Network: Learning Grasp Generators from Partial Point Clouds with Diffusion Models in SO(3)xR3
Joao Carvalho, An T. Le, Philipp Jahr +4
Grasping objects successfully from a single-view camera is crucial in many robot manipulation tasks. An approach to solve this problem is to leverage simulation to create large dat…
Motion Planning Diffusion: Learning and Adapting Robot Motion Planning with Diffusion Models
J. Carvalho, A. Le, P. Kicki +2
The performance of optimization-based robot motion planning algorithms is highly dependent on the initial solutions, commonly obtained by running a sampling-based planner to obtain…
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…
Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models
Joao Carvalho, An T. Le, Mark Baierl +2
Learning priors on trajectory distributions can help accelerate robot motion planning optimization. Given previously successful plans, learning trajectory generative models as prio…
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…
Residual Robot Learning for Object-Centric Probabilistic Movement Primitives
Joao Carvalho, Dorothea Koert, Marek Daniv +1
It is desirable for future robots to quickly learn new tasks and adapt learned skills to constantly changing environments. To this end, Probabilistic Movement Primitives (ProMPs) h…
Multimodal Uncertainty Reduction for Intention Recognition in Human-Robot Interaction
Susanne Trick, Dorothea Koert, Jan Peters +1
Assistive robots can potentially improve the quality of life and personal independence of elderly people by supporting everyday life activities. To guarantee a safe and intuitive i…