A versatile crawler robot platform designed for development, testing, and remote operation. Built with green aluminum alloy oxide, the chassis combines durability with a compact, lowprofile form suited to indoor and outdoor environments. Key benefits Reliable autonomous navigation: Integrated SLAM lidar and depth camera enable accurate mapping and obstacle avoidance for realworld testing and deployment. fidelity perception: HD camera plus depth sensing provide the visual and range data needed for computer vision, object detection, and FPV monitoring. Robust mobility and control: torque gear motors deliver steady traction and precise movement on uneven surfaces, reducing the need for repeated tuning. Ready for development: A powerful robot expansion board compatible with Yaboom simplifies sensor and actuator integration so teams can focus on software and experiments. Flexible programming and simulation: Native support for Python and ROS with Rviz, MoveIt, and Qt toolboxes allows seamless robotic arm control and realistic simulation workflows. Multiple control options: Operate the robot through a mobile app, a handle controller for FPV operation, or JupyterLab for online coding and remote experiments. Technical highlights and compatibility Chassis material: green aluminum alloy oxide for corrosion resistance and structural stability. Sensors: SLAM lidar, HD camera, and depth camera for combined mapping and perception. Actuation: torque gear motors for dependable drive performance. Electronics: robot expansion board compatible with Yaboom for easy hardware expansion and peripheral connection. Software: Python and ROS integration with support for Rviz, MoveIt, and Qt toolboxes; accessible via JupyterLab for interactive development. Practical use scenarios Autonomous mapping and inspection: Quickly create resolution maps of warehouses, test facilities, or complex indoor spaces while using FPV to verify routes and obstacles. Education and research: Use the platform in robotics courses or research labs to teach SLAM, perception, motion planning, and robotic arm control with handson programming in Python and ROS. Remote monitoring and prototyping: Deploy the crawler for remote visual inspection in confined or uneven areas while developing custom algorithms via JupyterLab and validating them in Rviz and MoveIt. This crawler platform combines rugged hardware and established software toolchains to accelerate development, testing, and deployment of mobile robotics projects.