A compact, performance development platform for learning, prototyping, and secondary development that combines readymade features with full programmability. Key benefits Readytorun interactive features: play target tracking, smart carrier, faceactivation, and group control scenarios out of the box to accelerate demonstrations and classroom lessons. Powerful compute and expandability: built around a Raspberry Pi 4B board for smooth image processing and realtime control, with Python support for custom scripts and experiments. Learn and build faster: abundant tutorials and opensource code make it easy to follow examples, modify behavior, and reuse components for projects. Accessible for all skill levels: dual control methods allow beginners to operate prebuilt functions and advanced users to develop complex behaviors via code. Practical for real projects: designed for sensor integration and visual picking tasks, making it suitable for robotics, automation, and STEM education. Core features and specifications Function: faceactivation, target tracking, smart carrier behavior, group control and other interactive game modes for testing perception and coordination. Compatibility: powered by a Raspberry Pi 4B board and compatible with Python development environments for rapid prototyping. Software: opensource example programs and stepbystep tutorials to support teaching, debugging, and feature expansion. Performance: sufficient compute for realtime vision tasks and control loops when paired with typical camera and sensor modules. Form and build: compact form factor and robust construction for classroom, lab, and workshop use. Typical applications Educational robotics: teach computer vision, control theory, and collaborative robotics with handson exercises using faceactivation and group control modes. Prototype automation systems: implement visual picking routines and smart carrier demonstrations to validate algorithms before scaling to production hardware. Sensor integration and research: attach environmental sensors or manipulators and use the Python API to collect data, test control strategies, and automate experiments. Why this product solves common problems Reduces setup time: builtin demonstrations and example code shorten the path from unboxing to meaningful results. Lowers learning barriers: clear tutorials and Python support let learners transition from simple use to custom development without changing platforms. Supports real testing: the combination of onboard compute and open interfaces enables practical evaluation of vision and sensordriven workflows. Included resources Stepbystep tutorials, example projects, and opensource code repositories to replicate demonstrations and extend functionality for custom applications. This platform provides a practical, welldocumented base for education, prototyping, and secondary development projects that require realtime vision, multiagent coordination, and flexible programming via Python.