Курс от Board Infinity This hands-on beginner course guides students through building intelligent robotic systems using Arduino Uno, basic electronics, and foundational AI-inspired control logic. You’ll start by understanding the core building blocks of a robot—sensing, decision-making, actuation, autonomy, and feedback loops—then set up the Arduino IDE, write your first sketches, and learn how the setup() and loop() structure governs robot behavior. Along the way, you’ll safely wire breadboards, power rails, sensors, and motors to bring your robots to life. From there, you’ll interface ultrasonic and IR sensors, DC motors, and servos to build sensor-driven robots that respond to their environment. You’ll implement threshold-based logic, then go beyond it by introducing state machines to structure more autonomous behaviors. You’ll build an obstacle-avoiding robot that scans multiple directions, compares distance readings, and selects clearer paths. The course then introduces basic fuzzy logic for smoother speed control from distance readings, and guides you through programming a line-following robot that uses IR sensors and proportional control for continuous feedback and correction. You’ll finish by connecting these foundational Arduino and control concepts to advanced AI robotics topics such as computer vision, SLAM, path planning, ROS, and machine learning, giving you a clear roadmap for further learning. Disclaimer: This is an independent educational resource created by Board Infinity for informational and educational purposes only. This course is not affiliated with, endorsed by, sponsored by, or officially associated with any company, organization, or certification body unless explicitly stated. The content provided is based on industry knowledge and best practices but does not constitute official training material for any specific employer or certification program. All company names, trademarks, service marks, and logos referenced are the property of their respective owners and are used solely for educational identification and comparison purposes.
2 модулей · 18 учебных материалов

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