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183.660 Mobile Robotics
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2024W, VU, 3.0h, 4.5EC

Properties

  • Semester hours: 3.0
  • Credits: 4.5
  • Type: VU Lecture and Exercise
  • Format: Blended Learning

Learning outcomes

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 + ROS2).

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.

Subject of course

  • 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)

 

Teaching methods

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

 

Mode of examination

Oral

Additional information

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


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

 

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Wed13:00 - 16:0002.10.2024 - 22.01.2025EI 11 Geodäsie HS - INF Lecture
Mobile Robotics - Single appointments
DayDateTimeLocationDescription
Wed02.10.202413:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed09.10.202413:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed16.10.202413:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed23.10.202413:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed30.10.202413:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed06.11.202413:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed13.11.202413:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed20.11.202413:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed27.11.202413:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed04.12.202413:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed11.12.202413:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed18.12.202413:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed08.01.202513:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed15.01.202513:00 - 16:00EI 11 Geodäsie HS - INF Lecture
Wed22.01.202513:00 - 16:00EI 11 Geodäsie HS - INF Lecture

Examination modalities

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.

Course registration

Not necessary

Curricula

Study CodeObligationSemesterPrecon.Info
066 515 Automation and Robotic Systems Mandatory elective
066 931 Logic and Computation Not specified
066 932 Visual Computing Not specified
066 937 Software Engineering & Internet Computing Mandatory elective
066 938 Computer Engineering Mandatory elective
066 938 Computer Engineering Mandatory elective

Literature

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

Continuative courses

Language

English