Product overview A rugged crawler robot platform designed for development, research, and field testing. The chassis is finished in green aluminum alloy oxide for strength, corrosion resistance, and a professional appearance. Builtin perception, actuation, and expansion hardware make this robot ready for autonomous navigation, manipulation, and simulation tasks out of the box. Why this robot matters Readytodevelop platform: Combines proven sensors and motors with open software support so you can focus on algorithms, applications, and testing rather than basic integration. Reliable performance on real terrain: torque gear motors and a crawler drive deliver stable motion and strong payload handling for sensors or manipulators. Flexible integration and expansion: A powerful robot expansion board simplifies connecting additional sensors, servos, and peripherals as your project grows. Key features and benefits Robust crawler design: Green aluminum alloy oxide construction gives durability and a lightweight profile suited for repeated field use. Advanced perception: SLAM lidar plus HD and depth cameras enable mapping, obstacle detection, and rich visual sensing for navigation and inspection tasks. Strong drive system: torque gear motors provide reliable motion and improved control on uneven surfaces or during manipulator operation. Expandable control hardware: The included robot expansion board supports multiple sensors and actuators, making it easier to prototype and scale systems. Python and ROS compatible: Full support for ROS and Python development environments accelerates deployment of navigation, manipulation, and perception stacks. Visualization and control toolboxes: Use Rviz, MoveIt, and Qt toolboxes for robotstate visualization, motion planning, and creating user interfaces. Crossplatform operation: Control the robot through a mobile app, a handheld controller for FPV operation, or JupyterLab for interactive online programming and testing. Compatibility and developer support Software: Compatible with ROSbased workflows, Python libraries, Rviz, MoveIt, and Qt toolboxes. JupyterLab support enables notebookdriven development and remote experimentation. Controls: Operate via mobile app, handle controller for firstpersonview driving, or programmatic control in Python and ROS. Practical applications Autonomous navigation research: Test SLAM and pathplanning algorithms in indoor and semistructured outdoor environments using the lidar and depth cameras. Field inspection and data collection: Use HD and depth cameras for visual inspection of equipment, inventory, or infrastructure while the crawler handles rough surfaces. Robotics education and prototyping: Rapidly prototype robotic arms, perception pipelines, and control interfaces using ROS toolboxes and the expansion board. What sets it apart Integrated sensor suite with SLAMcapable lidar and depth sensing Durable aluminum alloy crawler chassis for practical field use Open, developerfriendly software stack for fast experimentation and deployment Included functions Autonomous mapping and navigation support Visual and depth perception for object detection and scene understanding Expansionready hardware for servos, sensors, and custom modules Multiple control modes for field operation and remote programming This robot platform is built to bridge the gap between concept and deployment, offering a compact, expandable, and softwarefriendly solution for developers, researchers, and educators.