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Main Authors: Li, Hanbing, Cao, Xuewei, Zeng, Zhiwen, Wu, Yuhan, Zhang, Yanyong, Xia, Yan
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2604.01708
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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