49 citations · 193 across the 22 of their papers we have counts for
36 papers · 1 filter
Comparing Reconstruction- and Contrastive-based Models for Visual Task Planning
Constantinos Chamzas, Martina Lippi, Michael C. Welle +3
Learning state representations enables robotic planning directly from raw observations such as images. Most methods learn state representations by utilizing losses based on the rec…
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…
Bayesian Meta-Learning for Few-Shot Policy Adaptation Across Robotic Platforms
Ali Ghadirzadeh, Xi Chen, Petra Poklukar +3
Reinforcement learning methods can achieve significant performance but require a large amount of training data collected on the same robotic platform. A policy trained with expensi…
Graph-based Task-specific Prediction Models for Interactions between Deformable and Rigid Objects
Zehang Weng, Fabian Paus, Anastasiia Varava +3
Capturing scene dynamics and predicting the future scene state is challenging but essential for robotic manipulation tasks, especially when the scene contains both rigid and deform…
Learning Deep Energy Shaping Policies for Stability-Guaranteed Manipulation
Shahbaz Abdul Khader, Hang Yin, Pietro Falco +1
Deep reinforcement learning (DRL) has been successfully used to solve various robotic manipulation tasks. However, most of the existing works do not address the issue of control st…
Interpretability in Contact-Rich Manipulation via Kinodynamic Images
Ioanna Mitsioni, Joonatan Mänttäri, Yiannis Karayiannidis +2
Deep Neural Networks (NNs) have been widely utilized in contact-rich manipulation tasks to model the complicated contact dynamics. However, NN-based models are often difficult to d…