# Hexapod agent powered by Gemma4:e4b > Source: > Published: 2026-05-23 22:30:10+00:00 This is a submission for the Gemma 4 Challenge: Write About Gemma 4 I built an AI-powered Hexapod Robot capable of autonomous navigation and dynamic gait adjustment. The project solves the complexity of coordinating 18 servos to maintain stability across uneven terrain, creating an experience where the robot can 'reason' about its movement based on sensor feedback rather than relying on hard-coded patterns. hexapod_tcp.rs hexapod_video.rs I utilized the gemma4:e4b model. I chose the e4b model because it fits locally on my Mac Mini, yet provides the sophisticated spatial reasoning and logic precision required to translate high-level commands (e.g., "navigate to the red object") into explicit, coordinate-based gait adjustments and parameter generation. The hexapod server operates across 2 dedicated ports: hexapod_tcp.rs CMD_MOVE#FORWARD#SPEED50 ). The robot physically begins walking.Because LLMs do not possess a continuous, constant "stream" of consciousness, the agent actively polls its environment at regular intervals while the robot is in motion by repeatedly executing its sensory tools: hexapod_video.rs : The agent executes this tool to capture the latest frame from the onboard camera (protected via an ENV_LOCK ). The model analyzes the image matrix to determine whether a visual obstruction exists, such as a wall or a drop-off.hexapod_tcp.rs : To acquire precise, real-time distance data, the agent dispatches a telemetry request over the open TCP socket (e.g., GET_SONAR_DIST ). The tool awaits the hardware return payload, receives the integer distance data (e.g., 15cm ), and feeds that string back into the LLM context window for subsequent action evaluation.