Robust crawler platform designed for research, education, and field prototyping. The aluminum alloy oxide chassis provides a durable, lightweight foundation while the tracked design delivers stability and traction on varied surfaces. Key benefits Reliable mobility and protection: Trackbased drive and a corrosionresistant aluminum alloy oxide body reduce wear from outdoor or workshop use and support repeated testing. Accurate perception: SLAM lidar plus HD and depth cameras enable mapping, obstacle detection, and depthaware vision for navigation and manipulation tasks. Strong actuation and expansion: torque gear motors deliver consistent drive force, and a powerful robot expansion board provides I O and control capacity for sensors and manipulators. Flexible software and control options: Native support for Python and ROS allows you to build, simulate, and deploy algorithms using Rviz, MoveIt, and Qt toolboxes. Control from a mobile app, a handheld controller for FPVstyle operation, or JupyterLab for online programming. Features and specifications Chassis material and finish: Green aluminum alloy oxide for durability and a professional appearance. Sensors: SLAMcapable lidar for mapping and localization, HD camera for visual recording, and depth camera for 3D perception. Actuation: torque gear motors tuned for tracked locomotion and payload handling. Expansion and controller board: Powerful robot expansion board for motor control, sensor I O, and peripheral integration. Software compatibility: Python and ROS ready with Rviz, MoveIt, and Qt toolboxes supported for simulation and robotic arm control. Control interfaces: Mobile application, handheld controller for firstperson view operation, and JupyterLab online programming environment. How this product solves problems Reduces development time by combining reliable hardware and widely used software toolchains. Simplifies field testing with rugged construction and stable tracked mobility. Enables realistic simulation and precise manipulation through integrated sensors and ROS toolboxes. Supports multiple users and workflows from manual remote operation to advanced algorithm development. Practical use scenarios Research and classroom labs: Use ROS, Rviz, and MoveIt to teach SLAM, autonomous navigation, and robotic arm control, then validate algorithms on the physical platform. Field inspection and data collection: Deploy the crawler to explore confined or uneven areas while recording HD video and depth data for mapping and analysis. Prototype development: Integrate additional sensors or manipulators using the expansion board, program behaviors in Python or JupyterLab, and test in realworld environments. What you get in practice A versatile development platform that bridges simulation and reality with compatible software tools, robust sensing, and expandable hardware. Multiple control paths so teams with different skills can operate, test, and iterate efficiently. This crawler is suited for engineers, educators, and developers who need a compact, durable base for perception, navigation, and manipulation projects that works seamlessly with Python and ROS toolchains.