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Developer demonstrates local Qwen3 LLM agent driving Husky A300 mobile robot
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A developer shared on Reddit an engineering implementation that uses a local Qwen3 LLM agent to drive a Husky A300 mobile robot via ROS2 Nav2. It currently runs entirely in simulation, and the author says the same action-client/function-calling architecture can be migrated directly to the real robot. Architecturally, it adopts an asynchronous background task model: chat can still respond while the robot is navigating, and commands execute in the background and report results back; spatial coordinates are stored in the conversation context, with no external database needed. The author compiled llama.cpp from source and built it for GPU with CUDA 12.4, achieving real-time local inference with no cloud dependency.
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- LLM agent drives an AMR using Husky A300 + ROS2 Nav2 + local Qwen3
A developer on Reddit demonstrated driving a Husky A300 mobile robot with a local Qwen3 LLM agent through ROS2 Nav2: it uses an asynchronous background task architecture, so chat still responds during navigation, and llama.cpp was compiled with CUDA 12.4 for real-time local inference with no cloud dependency. Spatial coordinates are kept in the conversation context with no external database; it currently runs entirely in simulation, and the same action-client/function-calling architecture can be transferred directly to a physical robot.
Reddit r/robotics ·