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Freie Universität Bozen

Mobile robotics

Semester 2 · 47568 · Master in Industrie- und Maschineningenieurwesen · 5KP · EN


A mobile robot is an unmanned system that operates in unstructured and dynamic environments, with or without the oversight of a human. Applications of mobile robots include environmental monitoring; manufacturing logistics and production; search & rescue; construction; forestry management, agricultural monitoring and production; mining; marine measurement and monitoring; and aerospace operations. This course covers the fundamental principles of mobile robotics at an introductory level. The topics covered include: functional architecture of unmanned systems (electrical, mechanical and software); vehicle dynamics and modelling; common navigation sensors, state & disturbance estimation; low-level control; and trajectory generation. Laboratory exercises that use Matlab, Simulink and possibly ROS/Gazebo to control unmanned vehicles will be given.

Lehrende: Karl Dietrich von Ellenrieder

Vorlesungsstunden: 28
Laboratoriumsstunden: 18
Anwesenheitpflicht: Attendance at lectures and exercise sessions is strongly recommended.

Themen der Lehrveranstaltung
The basic principles of mobile robotics are presented.

Unterrichtsform
Classroom lectures and laboratory exercises.

Bildungsziele
Knowledge and understanding: 1. Applying basic principles to a broad range of dynamic system models (such as those typically learned in the 1st cycle). 2. Defining sensing and controller requirements for unmanned vehicles that operate in different conditions. 3. Understanding factors that affect system performance and stability. 4. Use of state space techniques for designing controllers and observers. Applying knowledge and understanding: 5. Analyzing, developing and presenting control & navigation systems for applications that span multiple disciplines through laboratory exercises, which complement the lectures. Making judgements: 6. On the choice of analytical and numerical tools to use in the lab exercises. This may require you to integrate knowledge, handle complexity, and formulate judgements with incomplete data. Communication skills: 7. Laboratory reports will require you justify your solutions/conclusions concisely (in clear and simple language). Learning Skills: 8. Students will be required to develop a proficiency in Matlab, Simulink and possibly ROS/Gazebo with a few in-class examples, but mostly on their own. This is intended to help students develop the ability to study in a manner that is largely self-directed or autonomous.

Art der Prüfung
- Formative assessment: Exercises: 18 hours total; ILOs assessed: 1 - 8; - Summative assessment: 40% exercises; ILOs assessed: 1-8; 60% final exam: 4 hours; ILOs assessed: 1-6.

Bewertungskriterien
Laboratory Exercises: Completeness and correctness of answers; level of understanding Written Final Exam: Completeness and correctness of answers. Students are required to receive an overall grade of greater than 60/100 points to pass the course.

Pflichtliteratur

Lecture notes and exercises will be available on Teams.



Weiterführende Literatur

Additional books and articles may be recommended by the instructor during the course.




Als PDF herunterladen

Ziele für nachhaltige Entwicklung
Diese Lehrtätigkeit trägt zur Erreichung der folgenden Ziele für nachhaltige Entwicklung bei.

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