Course Description

"Autonomous Navigation for Quadrotors" is an advanced-level course offered by TUMx, designed to equip students with the essential knowledge and skills required for developing autonomous flying robots. This comprehensive course delves into the fascinating world of quadrotor navigation, exploring cutting-edge techniques in 3D mapping, probabilistic state estimation, visual odometry, and linear control for UAVs. With a focus on practical application, students will engage in hands-on programming tasks using a browser-based quadrotor simulator, allowing them to implement and test their own flight algorithms.

What Students Will Learn

• Understanding of quadrotor flight principles and their diverse applications
• Mastery of 3D geometry concepts for aerial robotics
• Implementation of probabilistic state estimation techniques for drones
• Development of visual odometry and SLAM algorithms for quadrotors
• Application of linear control methods for UAV navigation
• Programming skills for quadrotor simulator environments
• Insight into autonomous flight algorithms and drone control systems

Pre-requisites

• Proficiency in linear algebra and 3D geometry
• Basic Python programming skills
• Familiarity with computer science, electrical engineering, or mechanical engineering concepts

Course Coverage

• 3D geometry and pose representation for flying robots
• Probabilistic state estimation techniques for quadrotors
• Visual odometry and SLAM algorithms for drone navigation
• 3D mapping and reconstruction using aerial robotics
• Linear control systems for UAV flight
• Implementation of extended Kalman filters (EKF) for state estimation
• PID controller design and tuning for quadrotor control
• Visual motion estimation techniques for drones
• Hands-on programming with a quadrotor simulator

Target Audience

This course is ideal for undergraduate and graduate students in computer science, electrical engineering, or mechanical engineering who are interested in autonomous navigation for flying robots. It is also suitable for professionals working in the fields of robotics, drone technology, or computer vision who want to expand their knowledge in quadcopter navigation and control systems.

Real-World Applications

• Developing autonomous drones for aerial filming and photography
• Creating UAV systems for remote visual inspection of industrial sites
• Designing quadrotors for automatic 3D reconstruction of buildings
• Implementing navigation algorithms for search and rescue operations
• Advancing research in the field of autonomous flying robots
• Improving drone control systems for various industries (agriculture, construction, etc.)
• Developing innovative solutions for drone delivery services
• Enhancing autonomous navigation capabilities for military and defense applications

Syllabus

1. Introduction to quadrotor navigation and applications
2. 3D geometry and pose representation
3. Probabilistic state estimation
4. Extended Kalman Filter (EKF) implementation
5. Visual odometry techniques
6. Simultaneous Localization and Mapping (SLAM) algorithms
7. 3D mapping and reconstruction
8. Linear control systems for quadrotors
9. PID controller design and tuning
10. Visual motion estimation
11. Hands-on programming with quadrotor simulator
12. Advanced topics in autonomous navigation for flying robots

Conclusion

This course offers a unique blend of theoretical knowledge and practical skills, making it an invaluable resource for anyone looking to excel in the field of autonomous navigation for quadrotors. By combining cutting-edge research with hands-on experience, students will gain a comprehensive understanding of the principles and techniques used in developing advanced drone control systems and autonomous flight algorithms.