881 citations · 1.6k across the 66 of their papers we have counts for
12 papers · 1 filter
Sequential Topological Representations for Predictive Models of Deformable Objects
Rika Antonova, Anastasiia Varava, Peiyang Shi +2
Deformable objects present a formidable challenge for robotic manipulation due to the lack of canonical low-dimensional representations and the difficulty of capturing, predicting,…
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…
Human-centered collaborative robots with deep reinforcement learning
Ali Ghadirzadeh, Xi Chen, Wenjie Yin +3
We present a reinforcement learning based framework for human-centered collaborative systems. The framework is proactive and balances the benefits of timely actions with the risk o…
Data-efficient visuomotor policy training using reinforcement learning and generative models
Ali Ghadirzadeh, Petra Poklukar, Ville Kyrki +2
We present a data-efficient framework for solving visuomotor sequential decision-making problems which exploits the combination of reinforcement learning (RL) and latent variable g…
Analytic Manifold Learning: Unifying and Evaluating Representations for Continuous Control
Rika Antonova, Maksim Maydanskiy, Danica Kragic +2
We address the problem of learning reusable state representations from streaming high-dimensional observations. This is important for areas like Reinforcement Learning (RL), which…
The effect of Target Normalization and Momentum on Dying ReLU
Isac Arnekvist, J. Frederico Carvalho, Danica Kragic +1
Optimizing parameters with momentum, normalizing data values, and using rectified linear units (ReLUs) are popular choices in neural network (NN) regression. Although ReLUs are pop…