Relocate¶
These datasets were generated with the AdroitHandRelocate-v1 environment, originally hosted in the hand_dapg repository. The objective of the task is to move a ball to a specific target position with a 24-DoF robotic hand. This domain was selected to measure the effect of a narrow expert data distributions and human demonstrations on a sparse reward, high-dimensional robotic manipulation task.
There are three types of datasets, two from the original paper[1] (human and expert), and another one introduced in D4RL[2] (cloned).
References¶
[1] Rajeswaran, Aravind, et al. ‘Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations’. CoRR, vol. abs/1709.10087, 2017, http://arxiv.org/abs/1709.10087.
[2] Fu, Justin, et al. ‘D4RL: Datasets for Deep Data-Driven Reinforcement Learning’. CoRR, vol. abs/2004.07219, 2020, https://arxiv.org/abs/2004.07219.
Content¶
ID |
Description |
|---|---|
25 human demonstrations provided in the DAPG repository |
|
Trajectories have expert data from a fine-tuned RL policy provided in the DAPG repository |
|
Data obtained by training an imitation policy on the demonstrations from |