Product overview A durable, modular robot tank designed for development, research, and field tasks. Built from green aluminum alloy oxide, this crawler offers a low profile and robust chassis for stable mobility and easy integration with sensors and manipulators. Key benefits Reliable mobility and load capacity: torque gear motors deliver consistent drive performance for rough terrain and extended demonstrations. Accurate perception and mapping: Integrated SLAM lidar plus HD and depth cameras enable realtime mapping, obstacle detection, and depthaware navigation. Ready for robotics development: A powerful robot expansion board supports onboard computation and sensor interfacing for advanced projects. Flexible control options: Work via a mobile app for quick tests, use a handle controller for FPV driving, or program online with JupyterLab for algorithm development and data analysis. ROS and Python compatibility: Out of the box support for Python and ROS toolboxes including Rviz, Movelt, and Qt to simulate, visualize, and control robotic arms and environments. Core features and specifications Chassis material: green aluminum alloy oxide for corrosion resistance and a professional finish. Perception suite: SLAM lidar plus HD camera and depth camera for combined visual and range sensing. Drive system: torque gear motors for dependable traction and precise speed control. Expansion and control: onboard robot expansion board to connect sensors, actuators, and compute modules. Software ecosystem: Python programming, ROS integration, and toolboxes Rviz, Movelt, and Qt for simulation and control workflows. Multiinterface operation: mobile app control, handle control for FPV, and JupyterLab online programming. Why this robot solves common problems Reduces development time by providing an integrated sensor and compute platform that connects directly to ROS and Python toolchains. Simplifies field testing with multiple control methods, so teams can switch between manual operation and automated runs without hardware changes. Improves mapping and navigation accuracy by combining SLAM lidar with HD and depth imaging, enabling safer autonomous movement in cluttered environments. Supports hardware expansion through a dedicated expansion board, avoiding intrusive rewiring and speeding up prototyping. Practical applications Research and education: Teach and prototype navigation, perception, and manipulation algorithms using ROS, Rviz, Movelt, and Python notebooks. Inspection and mapping: Perform indoor or structured outdoor mapping and visual inspections with SLAM lidar and depthassisted imaging. Robotics prototyping and demonstrations: Integrate custom arms or sensors via the expansion board and demonstrate realworld behaviors with FPV and appbased control. What makes it stand out Integrated sensor fusion with lidar and stereo depth gives richer situational awareness than cameraonly platforms. Sturdy aluminum alloy oxide body balances protection and weight for mobile experiments. Multiple control paths and standard software tool support allow teams with different workflows to adopt the platform quickly. Compatibility and integration notes Designed for Python and ROS based workflows and compatible with Rviz, Movelt, and Qt toolboxes for simulation and arm control. Expansion board provides standard interfaces for adding sensors, actuators, and compute modules without redesigning the chassis. Package suitability Ideal for university labs, development teams, robotics clubs, and field engineers needing a ready platform for mapping, navigation, and manipulation projects. Summary A versatile crawler platform that combines robust hardware, comprehensive sensing, and standard software tool support to accelerate development and field testing. The green aluminum alloy oxide chassis, SLAM lidar, HD and depth cameras, torque motors, and expansion board create a balanced foundation for research, inspection, and prototyping tasks while offering flexible control through mobile app, handle, or JupyterLab programming.