The Artificial Intelligence (AI) Hardware Lab (the most comprehensive smart hardware development facility in South China, equipped with service robots, intelligent aerial vehicles, smart carts, interactive robotic arms, STM32 and Arduino development platforms, AI optical motion capture systems, etc.). The lab provides students in AI, Data Science, and Big Data Technology programs with a fully equipped teaching, competition, research, and training facility. It supports foundational teaching objectives through courses including Python Fundamentals, Machine Learning, Deep Learning Algorithms, and Natural Language Processing. These programs cover both foundational practical training and secondary innovation development, cultivating students' hands-on skills, independent innovation capabilities, and readiness for relevant competitions.
The evolution of AI exhibits new characteristics such as deep learning, cross-disciplinary integration, and human-machine collaboration. In response to these trends, elective courses are designed around foundational knowledge and applications, as well as the construction and development of simple AI modules. The laboratory curriculum design consists of three modules: Fundamentals of Artificial Intelligence, Implementation of Simple AI Application Modules, and Development and Applications of AI Technologies. Through promoting teaching with competitions, it supports students in participating in relevant competitions, enabling them to understand the development history and core concepts of AI, describe the implementation processes of typical AI algorithms, and master technologies including visual recognition, natural language processing, and face recognition by building simple AI application modules.
Through practical case analysis and project-based design, students are guided to expand their thinking and explore typical intelligent systems. By guiding students to identify problems and attempt to solve them using AI methods, they gain initial exposure to the characteristics of AI, and experience firsthand the impact of intelligent technologies on everyday life and learning. This helps further motivate students' enthusiasm for learning and exploring new technologies and knowledge, while enhancing their ability to comprehensively apply information technology. By fully utilizing rich open-source hardware and AI application frameworks, realistic, real-world application scenarios are constructed. This approach fosters students' capacity for self-directed and inquiry-based learning, encouraging active exploration, bold experimentation, and the development of innovative thinking.
Industrial Robotic Arm:
Enables experimentation with fundamental algorithms including basic visual recognition, mechanical control, and machine learning. Materials: Aluminum alloy, carbon fiber; Tool connection type: M5*6; Payload capacity: 5 kg; Effective working radius: 700 mm; Degrees of freedom: 6; Repeatability accuracy: ±0.1 mm; Maximum end-effector speed: 1 m/s; Weight (without controller): 10.5 kg.
Drone Racing Development:
Supports learning microcontroller development including GPIO, I²C, PWM, and timer interrupts; enables study of core flight control algorithms like remote controller data parsing and attitude calculation; facilitates learning principles and practical application of complex algorithms such as laser altitude hold and OpenMV visual line following. Equipped with OpenMV optical flow and laser altitude hold modules, enabling laser altitude hold and visual hovering. Operates autonomously without remote control: one-button takeoff ascends to preset altitude, then follows mapped flight paths before auto-landing at destination. Supports flight controller replacement for secondary development. Enables targeted training for drone racing competitions.
Service Robot:
Features a full skill chain encompassing mouth, ears, eyes, legs, and brain, equipped with a microphone array, fisheye camera, HD camera, and steerable chassis. Meets training requirements for Artificial Intelligence application scenarios, enabling experimental teaching of algorithms like visual recognition and natural language processing.
AI Car Kit:
Features Python, OpenCV, and JupyterLab development environments for learning STM32 microcontroller programming. Supports game controller/PC/mobile app control and a 2D gimbal. Enables foundational sensor experiments like intelligent line following, infrared remote control, infrared obstacle avoidance, and ultrasonic obstacle avoidance using STM32 microcontrollers.
Arduino Development Kit:
Compatible with Arduino programming training courses. Primary hardware includes UNO mainboard and expansion boards, ULN2003 motor drivers, clock modules, various sensors, SG90 servos, Bluetooth modules, WiFi modules, and 76 other accessories. Supports diverse student design experiments with multiple configuration options.
AI Optical Motion Capture System:
Suitable for drone flight path capture, indoor precision positioning for drones (or vehicles), algorithm validation, swarm formation, and drone competition measurement. Also supports faculty research projects.
World Robot Contest
Global Artificial Intelligence Technology Innovation Competition
ACM International Collegiate Programming Contest
China Artificial Intelligence Innovation Competition
National Undergraduate Electronics Design Contest
China Undergraduate Mathematical Modeling Contest
National Undergraduate Smart Car Competition
China Robot Competition
China Engineering Robot Competition
Robot and Artificial Intelligence Competition
Guangdong Provincial Undergraduate Electronics Design Contest