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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.01708 |
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| _version_ | 1866908933328732160 |
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| author | Li, Hanbing Cao, Xuewei Zeng, Zhiwen Wu, Yuhan Zhang, Yanyong Xia, Yan |
| author_facet | Li, Hanbing Cao, Xuewei Zeng, Zhiwen Wu, Yuhan Zhang, Yanyong Xia, Yan |
| contents | Adaptation to complex tasks and multiple scenarios remains a significant challenge for a single robot agent. The ability to acquire organize, and switch between a wide range of skills in real time, particularly in dynamic environments, has become a fundamental requirement for embodied intelligence. We introduce OpenGo, an OpenClaw-powered embodied robotic dog capable of switching skills in real time according to the scene and task instructions. Specifically, the agent is equipped with (1) a customizable skill library with easy skill import and autonomous skill validation, (2) a dispatcher that selects and invokes different skills according to task prompts or language instructions, and (3) a self-learning framework that fine-tunes skills based on task completion and human feedback. We deploy the agent in Unitree's Go2 robotic dog and validate its capabilities in self-checking and switching of skills autonomously. In addition, by integrating Feishu-platform communication, we enable natural-language guidance and human feedback, allowing inexperienced users to control the robotic dog through simple instructions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_01708 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | OpenGo: An OpenClaw-Based Robotic Dog with Real-Time Skill Switching Li, Hanbing Cao, Xuewei Zeng, Zhiwen Wu, Yuhan Zhang, Yanyong Xia, Yan Robotics Artificial Intelligence Adaptation to complex tasks and multiple scenarios remains a significant challenge for a single robot agent. The ability to acquire organize, and switch between a wide range of skills in real time, particularly in dynamic environments, has become a fundamental requirement for embodied intelligence. We introduce OpenGo, an OpenClaw-powered embodied robotic dog capable of switching skills in real time according to the scene and task instructions. Specifically, the agent is equipped with (1) a customizable skill library with easy skill import and autonomous skill validation, (2) a dispatcher that selects and invokes different skills according to task prompts or language instructions, and (3) a self-learning framework that fine-tunes skills based on task completion and human feedback. We deploy the agent in Unitree's Go2 robotic dog and validate its capabilities in self-checking and switching of skills autonomously. In addition, by integrating Feishu-platform communication, we enable natural-language guidance and human feedback, allowing inexperienced users to control the robotic dog through simple instructions. |
| title | OpenGo: An OpenClaw-Based Robotic Dog with Real-Time Skill Switching |
| topic | Robotics Artificial Intelligence |
| url | https://arxiv.org/abs/2604.01708 |