X-OmniClaw Technical Report: A Unified Mobile Agent for Multimodal Understanding and Interaction
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arXiv
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| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866910244528979968 |
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| author | Ren, Xiaoming Zhen, Ru Li, Chao Song, Yang Hou, Qiuxia Zhang, Yanhao Liu, Peng Qi, Qi Zheng, Quanlong Wu, Qi Liao, Zhenyi Pan, Binqiang Ji, Haobo Lu, Haonan |
| author_facet | Ren, Xiaoming Zhen, Ru Li, Chao Song, Yang Hou, Qiuxia Zhang, Yanhao Liu, Peng Qi, Qi Zheng, Quanlong Wu, Qi Liao, Zhenyi Pan, Binqiang Ji, Haobo Lu, Haonan |
| contents | Inspired by the development of OpenClaw, there is a growing demand for mobile-based personal agents capable of handling complex and intuitive interactions. In this technical report, we introduce X-OmniClaw, a unified mobile agent designed for multimodal understanding and interaction in the Android ecosystem. This unified architecture of perception, memory, and action enables the agent to handle complex mobile tasks with high contextual awareness. Specifically, Omni Perception provides a unified multimodal ingress pipeline that integrates UI states, real-world visual contexts, and speech inputs, leveraging a temporal alignment module to decompose raw data into structured multimodal intent representations. Omni Memory leverages multimodal memory optimization to enhance personalized intelligence by integrating runtime working memory for task continuity with long-term personal memory distilled from local data, enabling highly context-aware and personalized interactions. Finally, Omni Action employs a hybrid grounding strategy that combines structural XML metadata with visual perception for robust interaction. Through Behavior Cloning and Trajectory Replay, the system captures user navigation as reusable skills, enabling precise direct-access execution. Demonstrations across diverse scenarios show that X-OmniClaw effectively enhances interaction efficiency and task reliability, providing a practical architectural blueprint for the next generation of mobile-native personal assistants. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_05765 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | X-OmniClaw Technical Report: A Unified Mobile Agent for Multimodal Understanding and Interaction Ren, Xiaoming Zhen, Ru Li, Chao Song, Yang Hou, Qiuxia Zhang, Yanhao Liu, Peng Qi, Qi Zheng, Quanlong Wu, Qi Liao, Zhenyi Pan, Binqiang Ji, Haobo Lu, Haonan Computer Vision and Pattern Recognition Inspired by the development of OpenClaw, there is a growing demand for mobile-based personal agents capable of handling complex and intuitive interactions. In this technical report, we introduce X-OmniClaw, a unified mobile agent designed for multimodal understanding and interaction in the Android ecosystem. This unified architecture of perception, memory, and action enables the agent to handle complex mobile tasks with high contextual awareness. Specifically, Omni Perception provides a unified multimodal ingress pipeline that integrates UI states, real-world visual contexts, and speech inputs, leveraging a temporal alignment module to decompose raw data into structured multimodal intent representations. Omni Memory leverages multimodal memory optimization to enhance personalized intelligence by integrating runtime working memory for task continuity with long-term personal memory distilled from local data, enabling highly context-aware and personalized interactions. Finally, Omni Action employs a hybrid grounding strategy that combines structural XML metadata with visual perception for robust interaction. Through Behavior Cloning and Trajectory Replay, the system captures user navigation as reusable skills, enabling precise direct-access execution. Demonstrations across diverse scenarios show that X-OmniClaw effectively enhances interaction efficiency and task reliability, providing a practical architectural blueprint for the next generation of mobile-native personal assistants. |
| title | X-OmniClaw Technical Report: A Unified Mobile Agent for Multimodal Understanding and Interaction |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2605.05765 |