We present a dataset with models of 14 articulated objects commonly found in human environments and with RGB-D video sequences and wrenches recorded of human interactions with them. The 358 interaction sequences total 67 minutes of human manipulation under varying experimental conditions (type of interaction, lighting, perspective, and background). Each interaction with an object is annotated with the ground-truth poses of its rigid parts and the kinematic state obtained by a motion-capture system. For a subset of 78 sequences (25 minutes), we also measured the interaction wrenches. The object models contain textured three-dimensional triangle meshes of each link and their motion constraints. We provide Python scripts to download and visualize the data. The data are available at https://turbo.github.io/articu lated-objects/ and hosted at https://zenodo.org/record/1036660/.
The RBO dataset REF is a collection of 358 RGB-D video sequences of humans manipulating 14 objects which are reconstructed as articulated 3D meshes.
The RBO dataset of articulated objects and interactions
The International Journal of Robotics Research
Mathematics Engineering Computer Science