AI Vision Quadruped Robot is an interactive quadruped platform for handson learning and experimentation in artificial intelligence and robotics. Combining realtime AI vision and flexible locomotion with a ROS based development environment, it is designed for hobbyists, students, and developers who want a practical, programmable robot platform. Key benefits Learn by doing: Integrated firstperson vision and ROS compatibility let you prototype and test machine vision, navigation, and control algorithms without building a platform from scratch. Realworld testing: AI vision supports target tracking, face detection, and line following, enabling immediate experiments and demonstrations. Versatile movement: An advanced linkage mechanism in the legs provides a range of gait patterns and the ability to traverse varied terrain for testing kinematics and locomotion strategies. Clear development path: Works with ROS for straightforward integration with common robotics tools, simulation workflows, and algorithm libraries. Core features AIpowered firstperson vision suitable for AI games and research tasks such as target tracking, face detection, and line following. Articulated quadruped legs using an advanced linkage mechanism to support multiple movement modes from walking to negotiating complex surfaces. ROS based educational platform for learning machine vision, robot kinematics, motion planning, and control system development. Interactive and programmable: Designed to be used as a learning and prototyping tool rather than a fixedfunction toy. Typical use scenarios University and classroom labs: Teach and demonstrate ROS concepts, machine vision pipelines, and robot kinematics with a readytouse physical platform. Hobbyist development and prototyping: Implement and test tracking algorithms, gait control, and perception modules in a compact, mobile robot. Demonstrations and competitions: Run AI game scenarios such as realtime target tracking, face detection challenges, and line following tests. Technical and practical notes Function: Combines vision and locomotion for integrated perceptionaction experiments. Compatibility: Built around ROS for easy integration with common robotics tools and educational resources. Performance: Realtime vision tasks and multigait locomotion support research and learning workflows. Form factor: Quadruped layout with articulated legs designed for repeated experimentation and movement testing. This platform is intended for users seeking a practical, programmable way to explore AI vision, robot kinematics, and motion control in real hardware.