Freiburg Block Tasks

Freiburg Block Tasks is a dataset for robot skill learning. It consists of two datasets. The first data set consisted of three simulated robot tasks: stacking (A), color pushing (B) and color stacking (C). The data set contains 300 multi-view demonstration videos per task. The tasks are simulated with PyBullet. Of these 300 demonstrations, 150 represent unsuccessful executions of the different tasks. The authors found it helpful to add unsuccessful demonstrations in the training of the embedding to enable training RL agents on it. Without fake examples, the distances in the embedding space for states not seen during training might be noisy. The test set contains the manipulation of blocks. Within the validation set, the blocks are replaced by cylinders of different colors. The second data set includes real-world human executions of the simulated robot tasks (A, B and C), as well as demonstrations for a task where one has to first separate blocks in order to stack them (D). For each task, there are 60 multi-view demonstration videos, corresponding to 24 minutes of interaction. In contrast to the simulated data set, the real demonstrations contain no unsuccessful executions and are of varying length. The test set contains blocks of unseen sizes and textures, as well as unknown backgrounds.