9 citations · 13 across the 3 of their papers we have counts for
8 papers
Graph-based Normalizing Flow for Human Motion Generation and Reconstruction
Wenjie Yin, Hang Yin, Danica Kragic +1
Data-driven approaches for modeling human skeletal motion have found various applications in interactive media and social robotics. Challenges remain in these fields for generating…
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…
Learning Stable Normalizing-Flow Control for Robotic Manipulation
Shahbaz Abdul Khader, Hang Yin, Pietro Falco +1
Reinforcement Learning (RL) of robotic manipulation skills, despite its impressive successes, stands to benefit from incorporating domain knowledge from control theory. One of the…
Stability-Guaranteed Reinforcement Learning for Contact-rich Manipulation
Shahbaz A. Khader, Hang Yin, Pietro Falco +1
Reinforcement learning (RL) has had its fair share of success in contact-rich manipulation tasks but it still lags behind in benefiting from advances in robot control theory such a…
Latent Space Roadmap for Visual Action Planning of Deformable and Rigid Object Manipulation
Martina Lippi, Petra Poklukar, Michael C. Welle +4
We present a framework for visual action planning of complex manipulation tasks with high-dimensional state spaces such as manipulation of deformable objects. Planning is performed…