NOC:Drone Systems and Control

Lecture 1 - Introduction to the course

Lecture 2 - Basics of drone operations

Lecture 3 - Tutorial 1: Vectors and coordinates

Lecture 4 - Tutorial 2: Vectors and coordinate transformations

Lecture 5 - Coordinate frames and transformations

Lecture 6 - Rigid body transformations

Lecture 7 - Dynamic model of multirotors

Lecture 8 - Drone sensors

Lecture 9 - Drone sensors - Context

Lecture 10 - MATLAB demonstration - drone sensors

Lecture 11 - Basics of Estimation

Lecture 12 - Kalman filtering Technique

Lecture 13 - Extended Kalman Filters (EKF)

Lecture 14 - Matlab Demonstration of Kalman Filtering

Lecture 15 - Matlab Demonstration of EKF

Lecture 16 - Introduction to Control Systems

Lecture 17 - Laplace Transforms

Lecture 18 - Matlab Demonstration of Laplace Transforms

Lecture 19 - Transfer Function Representation

Lecture 20 - Matlab Demonstration of Transfer Functions

Lecture 21 - Transient Response

Lecture 22 - Matlab Demonstration of Transient Response

Lecture 23 - Eigenvalues and Eigenvectors

Lecture 24 - State Space Representations

Lecture 25 - Matlab Demonstration of State Space Representations

Lecture 26 - Canonical Forms, State Transition Matrix (STM), Controllability, Observability

Lecture 27 - Examples on STM, Controllability and Observability

Lecture 28 - Pole Placement Methods

Lecture 29 - PID Controller

Lecture 30 - Drone Autopilot Design

Lecture 31 - Drone Autopilot Design

Lecture 32 - Drone Autopilot Design

Lecture 33 - MATLAB Demonstration of Autopilot Design

Lecture 34 - Global Path Planning

Lecture 35 - A* Algorithm for Global Path Planning

Lecture 36 - RRT & RRT* Algorithms Global Path Planning

Lecture 37 - Introduction to Sense-and-Avoidance (SaA)

Lecture 38 - Sensor for SAA, Trajectory Prediction, Decision making

Lecture 39 - Artificial Potential Field (APF)

Lecture 40 - Control Barrier Function (CBF)

Lecture 41 - Trajectory tracking with PID Control

Lecture 42 - Scenario Generation for UAV Operations

Lecture 43 - Scenario Generation with MATLAB Demonstrations

Lecture 44 - Autonomous Drone

Lecture 45 - Essential of Neural Network for Aerial Perception

Lecture 46 - Recurrent Neural Network (RNN) for Trajectory Prediction

Lecture 47 - Memory Neural Network (MNN) for Trajectory Prediction

Lecture 48 - Emerging Technology in UAV Swarm

Lecture 49 - Cooperative Multi-swarm UAV Operation for Forest Fire Fighting

Lecture 50 - Advanced Drones - Variable Pitch propeler Quadcopter