5 citations · 5 across the 1 of their papers we have counts for
4 papers
Residual Skill Policies: Learning an Adaptable Skill-based Action Space for Reinforcement Learning for Robotics
Krishan Rana, Ming Xu, Brendan Tidd +2
Skill-based reinforcement learning (RL) has emerged as a promising strategy to leverage prior knowledge for accelerated robot learning. Skills are typically extracted from expert d…
Critic Guided Segmentation of Rewarding Objects in First-Person Views
Andrew Melnik, Augustin Harter, Christian Limberg +3
This work discusses a learning approach to mask rewarding objects in images using sparse reward signals from an imitation learning dataset. For that, we train an Hourglass network…
Multiplicative Controller Fusion: Leveraging Algorithmic Priors for Sample-efficient Reinforcement Learning and Safe Sim-To-Real Transfer
Krishan Rana, Vibhavari Dasagi, Ben Talbot +2
Learning-based approaches often outperform hand-coded algorithmic solutions for many problems in robotics. However, learning long-horizon tasks on real robot hardware can be intrac…
Residual Reactive Navigation: Combining Classical and Learned Navigation Strategies For Deployment in Unknown Environments
Krishan Rana, Ben Talbot, Vibhavari Dasagi +2
In this work we focus on improving the efficiency and generalisation of learned navigation strategies when transferred from its training environment to previously unseen ones. We p…