Learning active manipulation to target shapes with model-free, long-horizon deep reinforcement learning
Matias Sivertsvik,Kirill Sumskiy,Ekrem Misimi,Matias Sivertsvik,Kirill Sumskiy,Ekrem Misimi
We investigate the active manipulation of objects using model-free and long-horizon DRL (Deep Reinforcement Learning) to achieve target shapes. Our proposed approach uses visual observations consisting of segmented images, to mitigate the sim-to-real gap. We address a long-horizon manipulation task requiring a sequence of accurate actions to achieve the target shapes using a robot arm with an RGB-...
