UAS Simulation
Niveau
Beginner
Learning outcomes of the courses/module
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.
- 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.
Prerequisites for the course
None
Course content
- 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).
- 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).
Recommended specialist literature
- 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.
- Marqués, P. & Ronch, A. D. (2017). Advanced UAV Aerodynamics, Flight Stability and Control. Wiley. ISBN: 978-1118928691. DOI: 10.1002/9781118928691.
Assessment methods and criteria
Portfolio tests
Language
English
Number of ECTS credits awarded
5
Share of e-learning in %
15
Semester hours per week
2.5
Planned teaching and learning method
Presentation, group work, discussion, exercises
Semester/trimester in which the course/module is offered
4
Name of lecturer
Academic year
Key figure of the course/module
4_5
Type of course/module
integrated lecture
Type of course
Compulsory