OpenGo: An OpenClaw-Based Robotic Dog with Real-Time Skill Switching

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Abstract: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.

Comments: 11 pages, 6 figures

Subjects:

Robotics (cs.RO); Artificial Intelligence (cs.AI)

Cite as: arXiv:2604.01708 [cs.RO]

(or arXiv:2604.01708v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2604.01708

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Hanbing Li [view email] [v1] Thu, 2 Apr 2026 07:19:51 UTC (3,118 KB)