Foundations of Autonomous Robotics and Path Planning

Autonomous systems are reshaping industries from logistics to self-driving cars, but breaking into this field requires a solid grasp of complex engineering concepts. This text-based course guides you through the fundamental principles of robotics without requiring expensive hardware. You will transition from a curious beginner to someone who understands how robots perceive their environment, make decisions, and execute precise movements, gaining the conceptual framework needed to work with modern robotic frameworks and algorithms. What you'll learn: Understand foundational robotics terminology, coordinate frames, and kinematics; Explore sensor fusion principles using data from LiDAR, cameras, and IMUs; Apply classic path planning algorithms like A* and Dijkstra in conceptual scenarios; Learn how robots localize themselves using odometry and basic SLAM concepts; Configure simple PID controllers to manage robotic movement and steering; Discover the architecture of modern middleware like ROS 2 for robotic communication. The course starts with essential definitions and mathematical foundations before progressing to perception, localization, and control strategies. You will read detailed explanations, analyze pseudocode, and work through conceptual design exercises. This course is designed for beginners with a basic background in mathematics and programming; no prior robotics experience or hardware is required. Start reading today to take your first step into the world of autonomous systems engineering.