YCB Object & Model Set
The YCB (Yale–CMU–Berkeley) Object and Model Set is a standardized set of 77 everyday physical objects with high-quality RGB-D scans and meshes, designed so manipulation results in different labs are reproducible on the same objects.
It is infrastructure, not a scored benchmark — but it underpins countless grasping and manipulation evaluations and the YCB-Video 6-DoF pose dataset.
Primary source →- Source
- Calli et al., IEEE R&A Magazine 2015
- Year
- 2015
- Scale
- 77 physical objects + RGB-D scans & meshes
- Gripper
- Object set
- Modality
- RGB-D meshes
- Best-known
- Standard physical object set — not a scored benchmark
- 77 physical objects with calibrated RGB-D scans + meshes
- Enables cross-lab reproducibility of manipulation results
- Basis for the YCB-Video pose benchmark
SIM = simulation result · HW = physical hardware. Image-wise accuracy is detection quality, not real-robot pick success. Figures cited from Calli et al., IEEE R&A Magazine 2015.
Related benchmarks
← Back to the grasping registerGraspNet-1Billion →
De-facto clutter benchmark · AnyGrasp current SOTA (AP)
Dex-Net 4.0 →
HW: 95% reliability · 300 MPPH (ABB YuMi)
SuctionNet-1Billion →
HW: 80.65% grasp success · 100% object clearance (their method)
Dex-Net 2.0 →
HW: 93% on adversarial · 99% precision on 40 novel objects (YuMi)