REVIEW 1 cited by
The RBO Dataset of Articulated Objects and Interactions
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
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 is available at https://tu-rbo.github.io/articulated-objects/ and hosted at https://zenodo.org/record/1036660/.
Forward citations
Cited by 1 Pith paper
-
Symbolic Intermediaries as a Linguistic-Numerical Interface for LLM-Driven Geometric Reasoning
A dual-agent LLM loop with symbolic-regression feedback improved planar mechanism synthesis Chamfer distances in most tested settings, but the headline genetic-algorithm comparison and critique-analysis claims are not...
Discussion (0). Continue with ORCID to comment.