Course

ATS - Autonomous Systems


PDF Course Catalog Deutsche Version: ATS

Version: 1 | Last Change: 25.09.2019 12:20 | Draft: 0 | Status: vom verantwortlichen Dozent freigegeben

Long name Autonomous Systems
Approving CModule ATS_BaET, ATS_BaTIN
Responsible
Prof. Dr. Chunrong Yuan
Professor Fakultät IME
Level Bachelor
Semester in the year summer semester
Duration Semester
Hours in self-study 69
ECTS 5
Professors
Prof. Dr. Chunrong Yuan
Professor Fakultät IME
Requirements Capability of algorithm analysis and implementation
Knowledge of signal processing and mathematics
Capability of software and project development
Basic knowledge of embedded software
Language German and English
Separate final exam Yes
Literature
Hertzberg: Mobile Roboter: Eene Einführung aus Sicht der Informatik, Springer Vieweg, 2012
Final exam
Details
Oral exam, with the option of written examination if necessary (e.g.: in case of a large number of participants)
Minimum standard
At least 50% with correct answers
Exam Type
Oral exam, with the option of written examination if necessary (e.g.: in case of a large number of participants)

Learning goals

Knowledge
Sensors
Wheel/motor sensors
Heading sensors
Positioning sensors
Cameras
Locomotion
Wheeled mobile robots
Legged mobile robots
Data processing and feature extraction
Edge detection
Line extraction
Point detection and description
Recognition and Modelling
Object detection
Place recognition
3D motion and structure estimation
Navigation
Localization
Mapping
Path planning
Expenditure classroom teaching
Type Attendance (h/Wk.)
Lecture 2
Tutorial (voluntary) 0
Special literature
keine/none
Special requirements
none
Accompanying material
Lecture slides
Separate exam
none

Learning goals

Skills
Teamwork: Development of systems with intelligent behaviours for autonomous interpretation of sensor data and real-time robot control. The goal is to realize prototypes with the required functions.
Expenditure classroom teaching
Type Attendance (h/Wk.)
Practical training 0.5
Tutorial (voluntary) 0
Special literature
keine/none
Special requirements
none
Accompanying material
Documents with task descriptions as well as instructions on project implementation
development tools and examples
Separate exam
Exam Type
working on projects assignment with your team e.g. in a lab)
Details
Evaluation of the achieved results based on presentations, live demonstrations, discussions as well as documentations in form of texts, source codes, graphic illustrations and video clips
Minimum standard
On-schedule delivery, presentation and demonstration of the realized systems according to task descriptions.

Learning goals

Skills
Sensor characterization
Feature extraction
Image matching and clustering
Image based place recognition
Motion analysis
Programming of robot behaviour
Expenditure classroom teaching
Type Attendance (h/Wk.)
Exercises (whole course) 1
Exercises (shared course) 1
Tutorial (voluntary) 0
Special literature
keine/none
Special requirements
Be prepared to use Python and install all the necessary software tools on one's own laptop
Accompanying material
Practical exercises
Example programs
Separate exam
none

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