AI vision robot tank kit with LIDAR and Python programming Overview A modular robot tank kit that combines camerabased AI vision, LIDAR sensing, and Python programmability. Designed for handson learning, rapid prototyping, and development of autonomous behaviors, the kit provides the core hardware and software interfaces needed to build navigation, mapping, and perception projects. Key benefits Learn and prototype faster: Pythonbased control lets users write and test algorithms quickly using familiar syntax and common robotics libraries. Reliable perception for real tasks: Integrated camera and LIDAR provide complementary sensing for object detection, distance measurement, and environment mapping. Flexible and extensible: Modular interfaces allow adding sensors, actuators, and compute modules to match education, hobby, or research needs. Realworld mobility: Tracked chassis delivers stable traction across varied indoor surfaces for repeatable testing and demonstrations. What it does Autonomous navigation: Combines vision and LIDAR data for obstacle detection and path planning. Mapping and localization: Supports building local maps for exploration and simple SLAM experiments. Object detection and tracking: Camerabased AI vision enables detection, classification, and following of targets. Remote control and scripting: Operate manually or run Python scripts for autonomous tasks and experiments. Important attributes Function: Tracks, steers, senses, and processes visual and distance data to enable autonomous and remotecontrolled robotics projects. Compatibility: Interfaces with common single board computers and microcontrollers via standard ports and communication protocols; works with widely used Python libraries for computer vision and robotics. Size: Compact footprint suitable for desktop development and indoor field testing. Materials: Robust mixedmaterial chassis designed for repeated assembly and component mounting. Performance: Realtime sensor streaming and motor control designed for responsive navigation and perception in typical indoor settings. Who will benefit Students learning robotics, computer vision, and Python programming. Makers and hobbyists building autonomous robots and perception demos. Researchers and developers prototyping navigation, mapping, and object recognition algorithms. Typical applications Educational labs: Stepbystep projects for Python programming, sensor integration, and AI vision exercises that demonstrate perception to action workflows. Autonomous navigation experiments: Test obstacle avoidance, path planning, and mapping algorithms using combined camera and LIDAR data. Indoor inspection and monitoring prototypes: Remote drive or autonomous sweep of indoor spaces to collect visual and distance data for analysis. What is included and expandable capability Tracked mobile chassis with drive motors and motor controllers. Onboard camera for visionbased perception. LIDAR sensor for distance measurements and obstacle detection. Accessible expansion ports for adding sensors, servos, or communication modules. Software examples and Python APIs to get started with vision, LIDAR, motor control, and data logging. Why choose this kit Practical balance of perception and mobility: Integrates both camera and LIDAR to support richer autonomy than vision or range sensing alone. Pythonfirst approach: Low barrier to entry for beginners and fast iteration for experienced developers. Modular design: Easy to modify and expand as projects grow from simple lessons to advanced prototypes. System requirements Compatible single board computer or microcontroller for onboard processing and Python runtime. Basic tools for assembly and a power source such as a compatible battery pack. Note on use This product is intended for educational, hobbyist, and development use. It provides hardware and software building blocks for learning and prototyping robotics applications using camera vision, LIDAR sensing, and Python programming.