Wichtiger Hinweis

 Die Vorlesungen am 4. und am 11. Juli fallen aufgrund von Dienstreisen aus. Bei der nächsten und letzten Vorlesung am 18. Juli findet die Präsentation der Programmieraufgaben statt. Bringen Sie hierzu bitte eine lauffähige Version Ihres Programmes auf einem Laptop mit.

Die Prüfungen finden am Freitag, den 20. Juli ab 15 Uhr statt. Neben dem offiziellen Prüfungstermin sind alternative Termine möglich. Bitte stimmen Sie sich hierzu per Mail mit Felix Govaers ab.

Weiter möchten wir Sie auf die anstehende Projektgruppe aufmerksam machen. Weiter Informationen hierzu werden ebenfalls in der Vorlesung am 18. Juli bekannt gegeben.

Lecture: Einführung in die Sensordatenfusion

Sensor data fusion is an omnipresent phenomenon that existed prior to its technological realization or the scientific reaction on it. In fact, all living creatures, including human beings, by nature or intuitively perform sensor data fusion. Each in their own way, they combine or fuse sensations provided by different and mutually complementary sense organs with knowledge learned from previous experiences and communications from other creatures. As a result, they produce a mental picture of their individual environment, the basis of behaving appropriately in their struggle to avoid harm or successfully reach a particular goal in a given situation. Sensor Data Fusion is the process of combining incomplete and imperfect pieces of mutually complementary sensor information in such a way that a better understanding of an underlying real-world phenomenon is achieved. Typically, this insight is either unobtainable otherwise or a fusion result exceeds what can be produced from a single sensor output in accuracy, relia- bility, or cost. Appropriate collection, registration and alignment, stochastic filtering, logical analysis, space-time integration, exploitation of redundancies, quantitative evaluation, and appropriate display are part of Sensor Data Fusion as well as the integration of related context information. Today, Sensor Data Fusion is evolving at a rapid pace and present in countless everyday systems and civilian products.

Course:

Exercises:

Other:

  • Term: Bachelor
  • Requirements:
  • Faculty: BA-INF 137
  • Effort: 2L+2E / 6CP
  • Exams: Information on the exams can be found in the Introduction Slides which are offered for download below. If you have further questions, please contact felix.govaers@fkie.fraunhofer.de.

Downloads

The slides and other downloads are available from within the university or via passwort. The password is announced or can be requested from Felix Govaers.

A monograph of Prof. Koch on Object Tracking and Sensor Data Fusion can be downloaded undefinedhere.

Slides

DateSlides
11.04.18undefinedLecture 1
18.04.18undefinedLecture 2
25.04.18undefinedLecture 3
02.05.18undefinedLecture 4
09.05.18undefinedLecture 5
30.05.18undefinedLecture 6
06.06.18undefinedLecture 7
13.06.18undefinedLecture 8
20.06.18undefinedLecture 9
27.06.18undefinedLecture 10
18.07.18undefinedLecture 12

Exercise Sheets

Date     File
02.05.18undefinedExercise 3
09.05.18undefinedExercise 4
30.05.18undefinedExcerise 5
06.06.18undefinedExercise 6

 

 

Information on Sensor Data Fusion