Product overview A versatile crawler tank platform built from green aluminum alloy oxide for a durable, sleek appearance and reliable field use. Designed for developers, researchers, and educators who need an integrated mobile robot that combines advanced sensing, robust actuation, and flexible software control. Key benefits Ready for autonomy and teleoperation: SLAM lidar plus HD and depth cameras enable mapping, obstacle detection, and depthaware navigation without additional sensors. Strong traction and payload capability: torque gear motors provide stable movement across varied surfaces while supporting sensors and manipulator hardware. Expandable control and I O: A powerful robot expansion board supports peripherals and custom hardware, simplifying prototyping and system integration. Familiar development environment: Native Python and ROS support with Rviz, Movelt, and Qt toolboxes means you can run simulations, develop motion plans, and control a robotic arm using standard tools. Multiple control modes: Operate via mobile app for quick tests, use handle control for immersive FPV driving, or program online with JupyterLab for more advanced workflows. Features and specifications Chassis: Crawler tank form factor constructed from green aluminum alloy oxide for a lightweight, corrosionresistant finish. Sensors: SLAM lidar for mapping and localization, HD camera for visual observation, and depth camera for 3D perception. Actuation: torque gear motors for reliable propulsion and controlled maneuvers. Control electronics: Integrated robot expansion board for motor control, sensor interfacing, and expansion of I O. Software: Python and ROS compatibility with Rviz, Movelt, and Qt toolboxes for simulation, visualization, and robotic arm control. Control options: Mobile app for remote operation, handle control for FPV effects, and JupyterLab for online programming and experimentation. Why this product solves common problems Speeds development: Preintegrated sensors and a ready expansion board reduce setup time compared to assembling components from scratch. Lowers integration risk: ROS toolchain compatibility and commonly used toolboxes enable direct use of existing packages and examples, simplifying testing and validation. Supports iterative workflows: Switch easily between teleoperation, FPV testing, and scripted experiments in JupyterLab without reconfiguring hardware. Scales with needs: Modular electronics and standard software stacks let you add manipulators, additional sensors, or custom control logic as projects grow. Practical use scenarios Indoor mapping and inspection: Use SLAM lidar and cameras to generate realtime maps of warehouses, labs, or test environments and inspect areas that are difficult to reach by foot. Robotic arm research and simulation: Combine ROS, Rviz, Movelt, and Qt toolboxes to develop, simulate, and validate robotic arm motion plans before deploying them on the physical platform. Remote field testing and FPV operation: Control the crawler via mobile app or handle for live FPV operation, collecting visual and depth data for remote surveys or prototype demonstrations. Compatibility and integration notes Supports Python and ROS workflows and is compatible with standard ROS toolboxes such as Rviz, Movelt, and Qt for visualization and control. Expansion board provides standard interfaces for motors, sensors, and external devices, enabling easy integration into existing robotic setups. Designed as a development platform suitable for research, education, and prototyping environments. What you get A crawler tank platform with integrated SLAM lidar, HD and depth cameras, torque gear motors, and a powerful expansion board ready for softwaredriven development and testing. This platform is intended for users who need a reliable, extensible mobile robot for mapping, perception, manipulation, and remote operation using widely adopted software tools.