9 papers
Demystifying When and Why VLAs Fail in Contact-Rich Tasks and How to Fix Them
Carlota Parés-Morlans, Nils Kuhn, Isabel Liu +2
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…
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…
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 DomÃnguez, Marco Iannotta, Abhishek Kashyap +21
The first WARA Robotics Mobile Manipulation Challenge, held in December 2024 at ABB Corporate Research in VästerÃ¥s, Sweden, addressed the automation of task-intensive and repetit…