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AtomicVLA: Unlocking the Potential of Atomic Skill Learning in Robots

This work proposes AtomicVLA, a unified planning-and-execution framework that jointly generates task-level plans, atomic skill abstractions, and fine-grained actions, and introduces a flexible routing encoder that automatically assigns dedicated atomic experts to new skills, enabling continual learning.

Likui Zhang, Tao Tang, Zhihao Zhan et al. · 19 citations · ⚡3

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