OpenGo: An OpenClaw-Based Robotic Dog with Real-Time Skill Switching
This addresses the problem of real-time skill switching for robotic dogs in dynamic environments, representing an incremental improvement with integration of existing components.
The researchers tackled the challenge of enabling a single robot agent to adapt to complex tasks and multiple scenarios by developing OpenGo, an OpenClaw-powered robotic dog that can switch skills in real-time based on scene and task instructions, deploying it on Unitree's Go2 robotic dog for validation.
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.