17 citations · 36 across the 18 of their papers we have counts for
3 papers · 2 filters
Hierarchical reinforcement learning for in-hand robotic manipulation using Davenport chained rotations
Francisco Roldan Sanchez, Qiang Wang, David Cordova Bulens +3
End-to-end reinforcement learning techniques are among the most successful methods for robotic manipulation tasks. However, the training time required to find a good policy capable…
Towards advanced robotic manipulation
Francisco Roldan Sanchez, Stephen Redmond, Kevin McGuinness +1
Robotic manipulation and control has increased in importance in recent years. However, state of the art techniques still have limitations when required to operate in real world app…
Dexterous Robotic Manipulation using Deep Reinforcement Learning and Knowledge Transfer for Complex Sparse Reward-based Tasks
Qiang Wang, Francisco Roldan Sanchez, Robert McCarthy +7
This paper describes a deep reinforcement learning (DRL) approach that won Phase 1 of the Real Robot Challenge (RRC) 2021, and then extends this method to a more difficult manipula…