5 citations · 13 across the 13 of their papers we have counts for
17 papers
ClothAtlas: Joint Garment Identification and State Estimation under Self-Occlusion
Jens Lundell, Alberta Longhini, Lei Shu +6
Garment manipulation requires inferring both garment identity and complete configuration from partial, self-occluded observations. This creates a chicken-and-egg problem: completin…
SoTa: Soft Tactile Skins for Dexterous Manipulation
Jingyun Yang, Baiyu Shi, Timothy Yu +6
A growing body of work suggests that tactile sensing gives robot policies contact information that complements vision in dexterous manipulation. However, visuo-tactile robot data r…
Direction-Scale Decomposition in Action Representation: Rethinking What to Tokenize for Vision-Language-Action Models
Yufei Duan, Hang Yin, Alberta Longhini +2
Action representation plays a central role in discrete-token vision-language-action (VLA) learning but remains underexamined. Under conventional pose-increment representations, act…
Demystifying When and Why VLAs Fail in Contact-Rich Tasks and How to Fix Them
Carlota Parés-Morlans, Nils Kuhn, Y. Isabel Liu +3
We address the problem of understanding when and why Vision-Language-Action models struggle with contact-rich manipulation tasks that require precise physical interaction. Prior wo…
Behavioral Mode Discovery for Fine-tuning Multimodal Generative Policies
Alberta Longhini, David Emukpere, Jean-Michel Renders +1
We address the problem of fine-tuning pre-trained generative policies with reinforcement learning (RL) while preserving the multimodality of their action distributions. Existing me…
Sim-to-Real Gentle Manipulation of Deformable and Fragile Objects with Stress-Guided Reinforcement Learning
Kei Ikemura, Yifei Dong, David Blanco-Mulero +3
Robotic manipulation of deformable and fragile objects presents significant challenges, as excessive stress can lead to irreversible damage to the object. While existing solutions…
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…
The First WARA Robotics Mobile Manipulation Challenge -- Lessons Learned
David Cáceres Domínguez, Marco Iannotta, Abhishek Kashyap +21
The first WARA Robotics Mobile Manipulation Challenge, held in December 2024 at ABB Corporate Research in Västerås, Sweden, addressed the automation of task-intensive and repetitiv…
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…
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…
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…
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…
EDO-Net: Learning Elastic Properties of Deformable Objects from Graph Dynamics
Alberta Longhini, Marco Moletta, Alfredo Reichlin +4
We study the problem of learning graph dynamics of deformable objects that generalizes to unknown physical properties. Our key insight is to leverage a latent representation of ela…
Elastic Context: Encoding Elasticity for Data-driven Models of Textiles
Alberta Longhini, Marco Moletta, Alfredo Reichlin +6
Physical interaction with textiles, such as assistive dressing, relies on advanced dextreous capabilities. The underlying complexity in textile behavior when being pulled and stret…
Textile Taxonomy and Classification Using Pulling and Twisting
Alberta Longhini, Michael C. Welle, Ioanna Mitsioni +1
Identification of textile properties is an important milestone toward advanced robotic manipulation tasks that consider interaction with clothing items such as assisted dressing, l…
Learning the tuned liquid damper dynamics by means of a robust EKF
Alberta Longhini, Michele Perbellini, Stefano Gottardi +3
The tuned liquid dampers (TLD) technology is a feasible and cost-effective seismic design. In order to improve its efficiency it is fundamental to find accurate models describing t…