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UAS Simulation

Niveau

Beginner

Lernergebnisse der Lehrveranstaltungen/des Moduls

Upon completing this course, students will be able to: - Understand the Principles of Drone Simulation: Explain the foundational concepts of drone simulation, including types of simulations (e.g., flight dynamics, sensor simulation, environmental interaction) and their applications in research, development, and training. - Operate Drone Simulation Software: Demonstrate proficiency using various drone simulation software and tools (e.g., Gazebo, AirSim, V-REP) for different use cases. - Model Drone Flight Dynamics: Model drone flight dynamics within simulation environments, accurately representing flight physics, including lift, drag, thrust, and gravity effects. - Simulate Sensor Data: Simulate sensor inputs (GPS, IMU, LiDAR, cameras) to test sensor fusion algorithms and data processing pipelines in a controlled environment. - Design Virtual Environments: Design and customize virtual environments for drone simulations (urban landscapes, natural terrains, obstacle courses) to replicate real-world scenarios. - Test and Validate Drone Systems: Utilize drone simulations to test and validate drone designs, flight control algorithms, and operational procedures, identifying potential issues before real-world deployment.

Voraussetzungen der Lehrveranstaltung

None

Lehrinhalte

- Introduction to Drone Simulation: Significance of simulation in drone design, testing, and training. Overview of simulation tools and environments, with a focus on Unreal Engine. - Basics of Unreal Engine for Drone Simulation: Introduction to Unreal Engine architecture, key features, and advantages for drone simulation. - Simulating Real-World Environments: Techniques for creating realistic simulation environments in Unreal Engine (terrain generation, environmental conditions, dynamic obstacles). - Drone Physics and Dynamics in Simulation: Implementing realistic drone physics and flight dynamics within the simulation (aerodynamic effects, propulsion, control systems). - Sensor Simulation: Simulating drone sensors (cameras, LiDAR, GPS) in Unreal Engine and integrating sensor data for navigation and obstacle detection. - Testing and Validation: Using simulations to test drone designs, flight control algorithms, and safety protocols. Discussion on the role of simulation in validating drone performance under various conditions. - Integration with Drone Development: Exploring the integration of simulation in the overall drone development lifecycle (initial design to deployment, iterative testing, refinement).

Empfohlene Fachliteratur

- Zipfel, P. H. (2014). Modeling and Simulation of Aerospace Vehicle Dynamics (3rd ed.). AIAA Education Series. ISBN: 978-1624102509. - Marqués, P. & Ronch, A. D. (2017). Advanced UAV Aerodynamics, Flight Stability and Control. Wiley. ISBN: 978-1118928691. DOI: 10.1002/9781118928691.

Bewertungsmethoden und -Kriterien

Portfolio tests

Unterrichtssprache

Englisch

Anzahl der zugewiesenen ECTS-Credits

5

E-Learning Anteil in %

15

Semesterwochenstunden (SWS)

2.5

Geplante Lehr- und Lernmethode

Presentation, group work, discussion, exercises

Semester/Trisemester, In dem die Lehrveranstaltung/Das Modul Angeboten wird

4

Name des/der Vortragenden

Studienjahr

Kennzahl der Lehrveranstaltung/des Moduls

4_5

Art der Lehrveranstaltung/des Moduls

Integrierte Lehrveranstaltung

Art der Lehrveranstaltung

Pflichtfach

Praktikum/Praktika