Free online courseAutonomous Drone Systems, Swarm Intelligence and Control Engineering

Course Description

Autonomous Drone Systems, Swarm Intelligence and Control Engineering is a free online course from NPTEL in the Technology and Programming category, focused on Robotics and Drones. It guides you from core principles of multirotor operation to the engineering methods used to model, estimate, control, and automate modern UAV behavior.

You will build a solid mathematical and geometric foundation for aerial robotics, including vectors, coordinate frames, and rigid-body transformations, then connect that theory to practical drone sensing and perception. The course develops essential estimation skills, moving from fundamentals to Kalman filtering and extended Kalman filtering, with hands-on MATLAB demonstrations that show how these tools are applied in UAV contexts.

On the control engineering side, you will progress through classic system analysis and design concepts such as Laplace transforms, transfer functions, transient response, eigenvalues, and state-space representations. You will learn how controllability and observability influence real design choices, and how techniques like pole placement and PID control translate into robust autopilot behavior. The course ties these ideas together through drone autopilot design workflows and MATLAB-based demonstrations.

Autonomy is extended beyond stabilization into navigation and decision-making. You will explore global path planning approaches and widely used algorithms such as A* and RRT, then move into sense-and-avoid concepts, including sensor considerations, trajectory prediction, and decision logic. Additional methods such as artificial potential fields and control barrier functions provide modern perspectives on safe motion planning and constraint-aware control, complemented by trajectory tracking strategies.

To round out a contemporary UAV skill set, the course introduces scenario generation for UAV operations and brings in learning-based elements for aerial perception and trajectory prediction, including neural networks and recurrent models. It also looks at emerging swarm technologies and cooperative multi-UAV operations, connecting foundational control to real-world multi-agent applications.