Datasets › ManiSkill
ManiSkill
ManiSkill is a large-scale learning-from-demonstrations benchmark for articulated object manipulation with visual input (point cloud and image). ManiSkill supports object-level variations by utilizing a rich and diverse set of articulated objects, and each task is carefully designed for learning manipulations on a single category of objects. ManiSkill is equipped with high-quality demonstrations to facilitate learning-from-demonstrations approaches and perform evaluations on common baseline algorithms. ManiSkill can encourage the robot learning community to explore more on learning generalizable object manipulation skills.
Source: ManiSkill: Learning-from-Demonstrations Benchmark for Generalizable Manipulation Skills
Image source: ManiSkill: Learning-from-Demonstrations Benchmark for Generalizable Manipulation Skills
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 38 papers for it but never published that list.
Dataset loaders archive 2025-07-28
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Tasks archive 2025-07-28
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License archive 2025-07-28
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Modalities archive 2025-07-28
Languages archive 2025-07-28
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Variants archive 2025-07-28
- ManiSkill
1 variant name, as the archive lists them.
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