After successful completion of the course, students are able to develop software components for autonomous mobile vehicles.The acquired competence enables the participants to realize filtering techniques especially for self-localization and path planning as well as to create nodes for the Robot Operating System (ROS).

After the first session, the tutors and the instructor will provide installation assistance for the software environment.
Alle Teilnehmer müssen sich im TISS zur LVA anmelden, um Zugang zum TUWEL Kurs zu erhalten.

• Behaviour Based Robotics (Breitenberg Vehicles)
• Sensors (Laser Scanner)
• Motion Model (Differential Drive)
• Mapping and Map Representation
• Self-localization:
  - Discrete Filter
  - Particle Filter
  - Extended Kalman Filter 
• SLAM
  - Fast-SLAM
  - Kalman based SLAM
• Planing
  - Local Planning (DWA, ...)
  - Global Planning (A*)

Workload estimation  (ECTS Breakdown): 112,5 Stunden = 4,5 ECTS

• Lecture time + exam (20 Stunden)
• Exercises (80 Stunden)
• Preperation for exam (12,5 Stunden)

The course consists of a theoretical and a practical (C++) part.

Video: Particle filter for self-localization in a stage enviroment

Screenshot of an implemented particle fitler and the simulation used with in the course.

The theoretical part of the course is examined orally at the end of the course, while the practical part, consisting of 6-7 exercises, is assessed regularly.
Due to the COVID infection process, it can lead to changes.

Probabilistic Robotics (2005)
Sebastian Thrun, Wolfram Burgard, Dieter Fox

LVA: Introduction to Mobile Robotics (2014)
http://ais.informatik.uni-freiburg.de/teaching/ss14/robotics/
Wolfram Burgard, Maren Bennewitz, Gian Diego Tipaldi, Luciano Spinello

Introduction to Autonomous Mobile Robots (2011)
Roland Siegwart, Illah Reza Nourbakhsh, Davide Scaramuzza

Principles of Robot Motion: Theory, Algorithms, and Implementations (2005)
Howie Choset, Kevin M. Lynch, Seth Hutchinson, George A. Kantor, Wolfram Burgard, Lydia E. Kavraki and Sebastian Thrun