Robust crawler platform built for development, research, and field tasks This tracked robot combines a durable green aluminum alloy oxide chassis with a compact crawler design for stable, allterrain mobility and longterm use. It is engineered to give developers and operators a reliable, modular base for sensing, navigation, and manipulation projects. Key benefits Durable, lightweight construction: Green aluminum alloy oxide chassis provides strength and corrosion resistance while keeping weight low for better mobility. Accurate mapping and navigation: Integrated SLAM lidar enables realtime mapping and autonomous navigation in complex environments. Advanced perception: HD camera plus depth camera deliver quality video and accurate depth sensing for obstacle detection, scene understanding, and computer vision workflows. Strong mobility and payload handling: torque gear motors provide precise speed control and the torque needed for rugged terrain and modest payloads. Expandable control and I O: A powerful robot expansion board enables custom sensors, actuators, and peripheral integration for experiments and product development. Full software integration: Native support for Python and ROS with toolboxes such as Rviz, MoveIt, and Qt for robotic arm control and realistic simulation, shortening the development cycle. Flexible control options: Operate the robot from a mobile app, a handheld controller for first person view operation, or program remotely via JupyterLab for iterative testing and data analysis. Function, compatibility, and performance Function: Autonomous navigation, remote exploration, and robotic arm manipulation with realworld simulation support. Compatibility: Works with Python and ROS ecosystems and common toolboxes including Rviz, MoveIt, and Qt for visualization, motion planning, and user interface development. Material and finish: Green aluminum alloy oxide chassis for a professional look and durable finish. Performance: SLAM lidar and HD plus depth cameras for perception, and torque gear motors for responsive locomotion. Practical use scenarios Research and education: Use as a teaching platform for ROS, SLAM, and robotic arm control. Integrate sensors and implement algorithms, then validate in realworld tests and simulations. Site inspection and monitoring: Perform autonomous or remote inspections in warehouses, industrial sites, or outdoor areas where tracked mobility and depth sensing help navigate uneven surfaces. Prototype development and robotics integration: Attach additional sensors or manipulators to the expansion board, test algorithms via JupyterLab, and visualize and refine motion using Rviz and MoveIt. What makes it stand out Combines rugged hardware and industrystandard software support to accelerate development from prototype to field tests. Multiple control and programming pathways let teams operate it the way they prefer, from appbased remote control to full programmatic access in Python and ROS. Modular expansion lets you add sensors, actuators, or custom electronics without redesigning the base platform. This crawler platform is designed for engineers, educators, and developers who need a versatile, wellintegrated robot base for mapping, perception, manipulation, and applied research.