9 citations · 33 across the 67 of their papers we have counts for
23 papers · 1 filter
Reframing Human-Robot Interaction Through Extended Reality: Unlocking Safer, Smarter, and More Empathic Interactions with Virtual Robots and Foundation Models
Yuchong Zhang, Yong Ma, Danica Kragic
This perspective reframes human-robot interaction (HRI) through extended reality (XR), arguing that virtual robots powered by large foundation models (FMs) can serve as cognitively…
Hybrid Imitation Learning: Teleoperation Augmentation Primitives that Policies Learn to Trigger
Jonne Van Haastregt, Bastian Orthmann, Michael C. Welle +2
What an operator can demonstrate bounds what imitation learning can learn. Teleoperation interfaces map the human body to the robot, so motions that are hard for a human, such as h…
Walking on the Fiber: A Simple Geometric Approximation for Bayesian Neural Networks
Alfredo Reichlin, Miguel Vasco, Danica Kragic
Bayesian Neural Networks provide a principled framework for uncertainty quantification by modeling the posterior distribution of network parameters. However, exact posterior infere…
Personalizing Emotion-aware Conversational Agents? Exploring User Traits-driven Conversational Strategies for Enhanced Interaction
Yuchong Zhang, Yong Ma, Di Fu +3
Conversational agents (CAs) are increasingly embedded in daily life, yet their ability to navigate user emotions efficiently is still evolving. This study investigates how users wi…
A Non-Adversarial Approach to Idempotent Generative Modelling
Mohammed Al-Jaff, Giovanni Luca Marchetti, Michael C Welle +5
Idempotent Generative Networks (IGNs) are deep generative models that also function as local data manifold projectors, mapping arbitrary inputs back onto the manifold. They are tra…
VBM-NET: Visual Base Pose Learning for Mobile Manipulation using Equivariant TransporterNet and GNNs
Lakshadeep Naik, Adam Fischer, Daniel Duberg +1
In Mobile Manipulation, selecting an optimal mobile base pose is essential for successful object grasping. Previous works have addressed this problem either through classical plann…
Randomized HyperSteiner: A Stochastic Delaunay Triangulation Heuristic for the Hyperbolic Steiner Minimal Tree
Aniss Aiman Medbouhi, Alejandro García-Castellanos, Giovanni Luca Marchetti +3
We study the problem of constructing Steiner Minimal Trees (SMTs) in hyperbolic space. Exact SMT computation is NP-hard, and existing hyperbolic heuristics such as HyperSteiner are…
Learning Hamiltonian Dynamics at Scale: A Differential-Geometric Approach
Katharina Friedl, Noémie Jaquier, Alyx Liao +1
Embedding physical intuition into network architectures allows the learning of dynamics that enforce fundamental properties, such as energy conservation laws, thereby leading to ph…
Real-Time Iteration Scheme for Diffusion Policy
Yufei Duan, Hang Yin, Danica Kragic
Diffusion Policies have demonstrated impressive performance in robotic manipulation tasks. However, their long inference time, resulting from an extensive iterative denoising proce…
Gesture First, LLM-Assisted Voice Complement: Exploring Multimodal Robot 'Puppeteer' Teleoperation Via Virtual Counterpart in Augmented Reality
Yuchong Zhang, Bastian Orthmann, Shichen Ji +3
Robot teleoperation via augmented reality (AR) offers a promising path toward more intuitive human-robot interaction (HRI). We present a head-mounted AR 'puppeteer' system in which…
DLO-Splatting: Tracking Deformable Linear Objects Using 3D Gaussian Splatting
Holly Dinkel, Marcel Büsching, Alberta Longhini +5
This work presents DLO-Splatting, an algorithm for estimating the 3D shape of Deformable Linear Objects (DLOs) from multi-view RGB images and gripper state information through pred…
FLoRA: Sample-Efficient Preference-based RL via Low-Rank Style Adaptation of Reward Functions
Daniel Marta, Simon Holk, Miguel Vasco +6
Preference-based reinforcement learning (PbRL) is a suitable approach for style adaptation of pre-trained robotic behavior: adapting the robot's policy to follow human user prefere…
Pushing Everything Everywhere All At Once: Probabilistic Prehensile Pushing
Patrizio Perugini, Jens Lundell, Katharina Friedl +1
We address prehensile pushing, the problem of manipulating a grasped object by pushing against the environment. Our solution is an efficient nonlinear trajectory optimization probl…
Learning Dexterous In-Hand Manipulation with Multifingered Hands via Visuomotor Diffusion
Piotr Koczy, Michael C. Welle, Danica Kragic
We present a framework for learning dexterous in-hand manipulation with multifingered hands using visuomotor diffusion policies. Our system enables complex in-hand manipulation tas…
Grasping a Handful: Sequential Multi-Object Dexterous Grasp Generation
Haofei Lu, Yifei Dong, Zehang Weng +3
We introduce the sequential multi-object robotic grasp sampling algorithm SeqGrasp that can robustly synthesize stable grasps on diverse objects using the robotic hand's partial De…
FLAME: A Federated Learning Benchmark for Robotic Manipulation
Santiago Bou Betran, Alberta Longhini, Miguel Vasco +2
Recent progress in robotic manipulation has been fueled by large-scale datasets collected across diverse environments. Training robotic manipulation policies on these datasets is t…
Advancing User-Voice Interaction: Exploring Emotion-Aware Voice Assistants Through a Role-Swapping Approach
Yong Ma, Yuchong Zhang, Di Fu +3
As voice assistants (VAs) become increasingly integrated into daily life, the need for emotion-aware systems that can recognize and respond appropriately to user emotions has grown…
Early Detection of Human Handover Intentions in Human-Robot Collaboration: Comparing EEG, Gaze, and Hand Motion
Parag Khanna, Nona Rajabi, Sumeyra U. Demir Kanik +3
Human-robot collaboration (HRC) relies on accurate and timely recognition of human intentions to ensure seamless interactions. Among common HRC tasks, human-to-robot object handove…
LLM-Driven Augmented Reality Puppeteer: Controller-Free Voice-Commanded Robot Teleoperation
Yuchong Zhang, Bastian Orthmann, Michael C. Welle +2
The integration of robotics and augmented reality (AR) presents transformative opportunities for advancing human-robot interaction (HRI) by improving usability, intuitiveness, and…
Humans Coexist, So Must Embodied Artificial Agents
Hannah Kuehn, Joseph La Delfa, Miguel Vasco +2
This paper introduces the concept of coexistence for embodied artificial agents and argues that it is a prerequisite for long-term, in-the-wild interaction with humans. Contemporar…
Human-Aligned Image Models Improve Visual Decoding from the Brain
Nona Rajabi, Antônio H. Ribeiro, Miguel Vasco +3
Decoding visual images from brain activity has significant potential for advancing brain-computer interaction and enhancing the understanding of human perception. Recent approaches…
Real-Time Operator Takeover for Visuomotor Diffusion Policy Training
Marco Moletta, Michael C. Welle, Nils Ingelhag +2
We present a Real-Time Operator Takeover (RTOT) paradigm that enables operators to seamlessly take control of a live visuomotor diffusion policy, guiding the system back to desirab…
Cloth-Splatting: 3D Cloth State Estimation from RGB Supervision
Alberta Longhini, Marcel Büsching, Bardienus P. Duisterhof +4
We introduce Cloth-Splatting, a method for estimating 3D states of cloth from RGB images through a prediction-update framework. Cloth-Splatting leverages an action-conditioned dyna…