Harmon: 言語記述からヒューマノイドの全身運動を生成
Harmon: Whole-Body Motion Generation of Humanoid Robots from Language Descriptions
人間の運動データを事前知識として活用し、視覚言語モデルの常識推論で編集・洗練することで、言語指示に沿った自然で多様なヒューマノイド全身運動を生成する手法を提案した。
著者: Zhenyu Jiang, Yuqi Xie, Jinhan Li, Ye Yuan, Yifeng Zhu, Yuke Zhu
分類: cs.RO, cs.AI
原文アブストラクト
Humanoid robots, with their human-like embodiment, have the potential to integrate seamlessly into human environments. Critical to their coexistence and cooperation with humans is the ability to understand natural language communications and exhibit human-like behaviors. This work focuses on generating diverse whole-body motions for humanoid robots from language descriptions. We leverage human motion priors from extensive human motion datasets to initialize humanoid motions and employ the commonsense reasoning capabilities of Vision Language Models (VLMs) to edit and refine these motions. Our approach demonstrates the capability to produce natural, expressive, and text-aligned humanoid motions, validated through both simulated and real-world experiments. More videos can be found at https://ut-austin-rpl.github.io/Harmon/.
