4 papers
CHEQ-ing the Box: Safe Variable Impedance Learning for Robotic Polishing
Emma Cramer, Lukas Jäschke, Sebastian Trimpe
Robotic systems are increasingly employed for industrial automation, with contact-rich tasks like polishing requiring dexterity and compliant behaviour. These tasks are difficult t…
Contextualized Hybrid Ensemble Q-learning: Learning Fast with Control Priors
Emma Cramer, Bernd Frauenknecht, Ramil Sabirov +1
Combining Reinforcement Learning (RL) with a prior controller can yield the best out of two worlds: RL can solve complex nonlinear problems, while the control prior ensures safer e…
Combining Automated Optimisation of Hyperparameters and Reward Shape
Julian Dierkes, Emma Cramer, Holger H. Hoos +1
There has been significant progress in deep reinforcement learning (RL) in recent years. Nevertheless, finding suitable hyperparameter configurations and reward functions remains c…
Tracking Object Positions in Reinforcement Learning: A Metric for Keypoint Detection (extended version)
Emma Cramer, Jonas Reiher, Sebastian Trimpe
Reinforcement learning (RL) for robot control typically requires a detailed representation of the environment state, including information about task-relevant objects not directly…