mlsanityData to 14 Oct 2026

SCENEREPLICA: Benchmarking Real-World Robot Manipulation by Creating Replicable Scenes

arXiv 2306.15620 ↗First posted 27 Jun 2023cs.RO cs.CV cs.LGcited by 9

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Abstract (arXiv)

We present a new reproducible benchmark for evaluating robot manipulation in the real world, specifically focusing on pick-and-place. Our benchmark uses the YCB objects, a commonly used dataset in the robotics community, to ensure that our results are comparable to other studies. Additionally, the benchmark is designed to be easily reproducible in the real world, making it accessible to researchers and practitioners. We also provide our experimental results and analyzes for model-based and model-free 6D robotic grasping on the benchmark, where representative algorithms are evaluated for object perception, grasping planning, and motion planning. We believe that our benchmark will be a valuable tool for advancing the field of robot manipulation. By providing a standardized evaluation framework, researchers can more easily compare different techniques and algorithms, leading to faster progress in developing robot manipulation methods.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 33 of its 45 references that are in the map. First posted on arXiv 27 Jun 2023.

Builds on

33 of 45 references.

References · 33

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21 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 2; 2026: 5.

9 papers.