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


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