9 citations · 33 across the 67 of their papers we have counts for
22 papers · 1 filter
Can Transformers Smell Like Humans?
Farzaneh Taleb, Miguel Vasco, Antônio H. Ribeiro +2
The human brain encodes stimuli from the environment into representations that form a sensory perception of the world. Despite recent advances in understanding visual and auditory…
Reducing Variance in Meta-Learning via Laplace Approximation for Regression Tasks
Alfredo Reichlin, Gustaf Tegnér, Miguel Vasco +3
Given a finite set of sample points, meta-learning algorithms aim to learn an optimal adaptation strategy for new, unseen tasks. Often, this data can be ambiguous as it might belon…
The 1st InterAI Workshop: Interactive AI for Human-centered Robotics
Yuchong Zhang, Elmira Yadollahi, Yong Ma +3
The workshop is affiliated with 33nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN 2024) August 26~30, 2023 / Pasadena, CA, USA. It is designed…
A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics
Katharina Friedl, Noémie Jaquier, Jens Lundell +2
By incorporating physical consistency as inductive bias, deep neural networks display increased generalization capabilities and data efficiency in learning nonlinear dynamic models…
Feature Extractor or Decision Maker: Rethinking the Role of Visual Encoders in Visuomotor Policies
Ruiyu Wang, Zheyu Zhuang, Shutong Jin +3
An end-to-end (E2E) visuomotor policy is typically treated as a unified whole, but recent approaches using out-of-domain (OOD) data to pretrain the visual encoder have cleanly sepa…
Relative Representations: Topological and Geometric Perspectives
Alejandro García-Castellanos, Giovanni Luca Marchetti, Danica Kragic +1
Relative representations are an established approach to zero-shot model stitching, consisting of a non-trainable transformation of the latent space of a deep neural network. Based…
HyperSteiner: Computing Heuristic Hyperbolic Steiner Minimal Trees
Alejandro García-Castellanos, Aniss Aiman Medbouhi, Giovanni Luca Marchetti +2
We propose HyperSteiner -- an efficient heuristic algorithm for computing Steiner minimal trees in the hyperbolic space. HyperSteiner extends the Euclidean Smith-Lee-Liebman algori…
Puppeteer Your Robot: Augmented Reality Leader-Follower Teleoperation
Jonne van Haastregt, Michael C. Welle, Yuchong Zhang +1
High-quality demonstrations are necessary when learning complex and challenging manipulation tasks. In this work, we introduce an approach to puppeteer a robot by controlling a vir…
Unfolding the Literature: A Review of Robotic Cloth Manipulation
Alberta Longhini, Yufei Wang, Irene Garcia-Camacho +9
The realm of textiles spans clothing, households, healthcare, sports, and industrial applications. The deformable nature of these objects poses unique challenges that prior work on…
Hyperbolic Delaunay Geometric Alignment
Aniss Aiman Medbouhi, Giovanni Luca Marchetti, Vladislav Polianskii +4
Hyperbolic machine learning is an emerging field aimed at representing data with a hierarchical structure. However, there is a lack of tools for evaluation and analysis of the resu…
Vision Beyond Boundaries: An Initial Design Space of Domain-specific Large Vision Models in Human-robot Interaction
Yuchong Zhang, Yong Ma, Danica Kragic
The emergence of large vision models (LVMs) is following in the footsteps of the recent prosperity of Large Language Models (LLMs) in following years. However, there's a noticeable…
Will You Participate? Exploring the Potential of Robotics Competitions on Human-centric Topics
Yuchong Zhang, Miguel Vasco, Mårten Björkman +1
This paper presents findings from an exploratory needfinding study investigating the research current status and potential participation of the competitions on the robotics communi…
Visual Action Planning with Multiple Heterogeneous Agents
Martina Lippi, Michael C. Welle, Marco Moletta +3
Visual planning methods are promising to handle complex settings where extracting the system state is challenging. However, none of the existing works tackles the case of multiple…
Low-Cost Teleoperation with Haptic Feedback through Vision-based Tactile Sensors for Rigid and Soft Object Manipulation
Martina Lippi, Michael C. Welle, Maciej K. Wozniak +2
Haptic feedback is essential for humans to successfully perform complex and delicate manipulation tasks. A recent rise in tactile sensors has enabled robots to leverage the sense o…
A Robotic Skill Learning System Built Upon Diffusion Policies and Foundation Models
Nils Ingelhag, Jesper Munkeby, Jonne van Haastregt +3
In this paper, we build upon two major recent developments in the field, Diffusion Policies for visuomotor manipulation and large pre-trained multimodal foundational models to obta…
Mind Meets Robots: A Review of EEG-Based Brain-Robot Interaction Systems
Yuchong Zhang, Nona Rajabi, Farzaneh Taleb +4
Brain-robot interaction (BRI) empowers individuals to control (semi-)automated machines through their brain activity, either passively or actively. In the past decade, BRI systems…
LM2D: Lyrics- and Music-Driven Dance Synthesis
Wenjie Yin, Xuejiao Zhao, Yi Yu +3
Dance typically involves professional choreography with complex movements that follow a musical rhythm and can also be influenced by lyrical content. The integration of lyrics in a…
Standardization of Cloth Objects and its Relevance in Robotic Manipulation
Irene Garcia-Camacho, Alberta Longhini, Michael Welle +3
The field of robotics faces inherent challenges in manipulating deformable objects, particularly in understanding and standardising fabric properties like elasticity, stiffness, an…
AdaFold: Adapting Folding Trajectories of Cloths via Feedback-loop Manipulation
Alberta Longhini, Michael C. Welle, Zackory Erickson +1
We present AdaFold, a model-based feedback-loop framework for optimizing folding trajectories. AdaFold extracts a particle-based representation of cloth from RGB-D images and feeds…
Interactive Perception for Deformable Object Manipulation
Zehang Weng, Peng Zhou, Hang Yin +4
Interactive perception enables robots to manipulate the environment and objects to bring them into states that benefit the perception process. Deformable objects pose challenges to…
Goal-Conditioned Reinforcement Learning from Sub-Optimal Data on Metric Spaces
Alfredo Reichlin, Miguel Vasco, Hang Yin +1
We study the problem of learning optimal behavior from sub-optimal datasets for goal-conditioned offline reinforcement learning under sparse rewards, invertible actions and determi…
DexDiffuser: Generating Dexterous Grasps with Diffusion Models
Zehang Weng, Haofei Lu, Danica Kragic +1
We introduce DexDiffuser, a novel dexterous grasping method that generates, evaluates, and refines grasps on partial object point clouds. DexDiffuser includes the conditional diffu…