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Introduction to the HACMan++ Long-Horizon Manipulation Framework

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Guyuehome introduced the HACMan++ framework, which targets long-horizon robotic manipulation for six-dimensional object rearrangement. According to the introduction, HACMan++ decomposes actions into three parts: selecting motion primitives, anchoring contact points and continuous parameters on the point cloud, and making unified decisions using a per-point, per-primitive evaluation map. On this basis, the framework achieves closed-loop chaining of pushing, grasping, moving, and placing.

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  1. HACMan++: Spatially Anchored Motion Primitives for Long-Horizon Robotic Manipulation

    HACMan++ targets long-horizon manipulation for six-dimensional object rearrangement, decomposing actions into three parts: selecting a primitive, anchoring a placement point on the point cloud, and continuous parameters, with unified decision-making via a per-point, per-primitive evaluation map. On this basis, the framework achieves closed-loop chaining of pushing, grasping, moving, and placing.

    Guyuehome ·

Related topics

Grasping and manipulationRobot models and learningResearch papers

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