XBot-Omni:身体理解と対話のためのオムニモーダルモデル
XBot-Omni: An Omni-Modal Model for Embodied Understanding and Interaction
テキスト・画像・音声・動画を入力に、発話・身体動作・表情を統合して生成するThinker-Talker-Actor構成のロボット向けオムニモーダルモデルを提案し、7つのベンチマークで理解と動作生成の性能を検証した。
詳しい要約
1. どんなもの?
2. 先行研究と比べてどこがすごい?
3. 技術・手法の肝は?
4. どうやって有効だと検証した?
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著者: Kerui Gu, Xing Fu, Shuoyang Sun, Cheng Peng, Jingru Duan, Huayu Gu, Zhenyu Chen, Jiaxin Huang, Cheng Wen, Rui Zhen, Kairui Chen, Zhihui Peng, Shaoli Huang
分類: cs.RO
原文アブストラクト
Embodied interaction requires an agent to integrate multimodal perception with verbal and nonverbal behaviors to effectively communicate its intentions, including speech, body motion, and facial expressions. We present XBot-Omni, a Thinker--Talker--Actor architecture that extends the Omni paradigm to robotic modalities, including body motion and facial expressions, with ``X'' representing the extensibility to robotic-specific modalities. The Thinker processes text, images, audio, and video to formulate contextually appropriate responses, which are then realized by the Talker and Actor through speech and coordinated bodily expressions, respectively. In this report, we innovatively introduce the concept of ``Actor'' as a dedicated component for embodied agents: a coordinated, streaming module that leverages the native representations of the Thinker and Talker within an end-to-end pipeline, introducing only modest latency overhead. This unified architecture enables multimodal generation conditioned on omni-modal inputs directly to prevent information loss in staged designs. We comprehensively evaluate XBot-Omni across seven benchmarks, demonstrating strong multimodal understanding capabilities on both general-domain and robot-centric videos, as well as high-quality, natural, and well-coordinated motion generation. Furthermore, our results validate its capability to generate embodied multimodal responses directly from omni inputs, meeting the diverse requirements of embodied interaction. XBot-Omni enables robots not only to perceive the omni world but also to express themselves through speech and bodily behaviors, extending Omni models from conversational interaction to embodied communication in physical environments.
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