Internship 2025: Autonomous Driving: Unterschied zwischen den Versionen
Zur Navigation springen
Zur Suche springen
| Zeile 64: | Zeile 64: | ||
* Project presentation in the wiki | * Project presentation in the wiki | ||
* Daily backup of work results in SVN | * Daily backup of work results in SVN | ||
* Dokument daily the [ | * Dokument daily the [https://svn.hshl.de/svn/HSHL_Projekte/trunk/JetRacer/USER/Shaaban/Stundennachweis_Shaaban.xlsx | ||
|Stundennachweis/timesheet] at start end of work in SVN. | |||
*[[Praxissemester|Information on Praxissemester]] | *[[Praxissemester|Information on Praxissemester]] | ||
*[[Studentische_Arbeiten_bei_Prof._Schneider|Student work with Prof. Schneider]] | *[[Studentische_Arbeiten_bei_Prof._Schneider|Student work with Prof. Schneider]] | ||
Version vom 20. Oktober 2025, 07:32 Uhr
| Autoren: | Mazen Mohamed Hussein Shaaban |
| Art: | Praxissemester |
| Dauer: | 15.10.2025 bis 04.02.2026 |
| Modul: | Internship/Exchange Semester, ELE-B-2-5.01 |
| Arbeitszeit: | 39,83 h/w, Anwesenheitspflicht im Labor |
| Betreuer: | Prof. Dr.-Ing. Schneider |
| Prüfungsform: | Modulabschlussprüfung als Hausarbeit (Praxisbericht, Umfang 20 Seiten) und mündliche Prüfungsleistung (Präsentation, 15 Minuten) |
| Mitarbeiter: | Marc Ebmeyer, Tel. 847 |
| Begrüßung: | 15.10.25 um 8:30 Uhr im Büro von Marc Ebmeyer |
Introduction
A model car (scale 1:10) equipped with a different sensors should
- drive autonomously in the right lane,
- avoid obstacles,
- react on sign and crossroads and
- parc autonomously.
Usually this can done by conventional algorithms (image processing, LiDAR object detection and sensor data fusion) or artificial intelligence (AI) (see Fig. 1). Choose a topic, analyze the possible solutions an solve task.
Task list
- Program the Jetson Nano on the JetRacer/JetRacer:_ROS_AI_Kit model based via MATLAB®/Simulink
- Read the sensor data (LiDAR, Video).
- Steer and change throttle.
- Evaluation of the solutions using a morphological box (Zwicky box)
- Implementation the most promising solution with MATLAB®
- First realise autonomous lane keeping. Optional add
- avoid obstacles
- traffic sign detection
- right of way at intersections
- autonomous parking
- Compare a classic approach to AI by technical characteristics.
- Set up requirements for the system
- Research on solutions for the task
- Evaluate the results based on technical features
- Discussion of the results
- Testing of the system requirements - proof of functionality
- Scientific documentation as a wiki article with an animated gif
Knowledge Requirements
The project requires prior knowledge in some but not all of the following subject areas. If you do not meet the requirements, the task can be individually adapted based on your previous knowledge.
- Model making (e. g. woodworking, metalworking, CAD, 3D printing)
- MATLAB®/Simulink
- Robotics
- Control technology
- Sourcecode versioning with SVN
- Documentation with Word and in the HSHL Wiki.
Requirements for scientific work
- Scientific approach (project plan, etc.), useful article: Create Gantt chart
- Weekly progress reports (informative), update the table Meeting Minutes in conversation with Prof. Schneider
- Project presentation in the wiki
- Daily backup of work results in SVN
- Dokument daily the [https://svn.hshl.de/svn/HSHL_Projekte/trunk/JetRacer/USER/Shaaban/Stundennachweis_Shaaban.xlsx
|Stundennachweis/timesheet] at start end of work in SVN.
SVN-Repository
https://svn.hshl.de/svn/HSHL_Projekte/trunk/JetRacer
Internship Timetable:
https://svn.hshl.de/svn/HSHL_Projekte/trunk/JetRacer/USER/Shaaban/Stundennachweis_Shaaban.xlsx
→ zurück zum Hauptartikel: Studentische Arbeiten