Significance of the proposed Master thesis
The use of autonomous vehicles is vital in the manufacturing and distribution operations. The automated guided vehicles (AGVs) provide reliable and efficient product handling in several industrial applications.
Goals of the proposed Master thesis
In this Master thesis, we are aiming a deep learning-based solution for pallet detection and position tracking. The process of data augmentation will also be included in this Master thesis. On top of that is the integration of defect detection in the pallets, which is already available.
Planned steps with estimated time
- Literature review and programming language background (30 days)
- understanding of dataset (obtaining 2D images by converting the rangedata polar to cartesian coordinates and resizing the resultant images) (15 days)we will use the publicly available “2D Laser Rangefinder dataset”.
- Suitable possible solutions for the given problem (45 days)One possible solution is Faster R-CNN. In addition to Faster R-CNN, we will try other possible solutions.
- Program a Graphical user interface (GUI) (30days)Lastly, for the successful completion of the Master thesis a professional GUI with embedded solution is required.
- Writing Master thesis (60 days)Writing a master thesis report in English or German.
- Interest, motivation and knowledge in supervised machine learning methods.
- Programming skills in Python with following deep-learning libraries.o TensorFlow
- o Keras
- • Proficient use of scientific work
Begin and duration:
Immediately , 6 months
Dr. Ing. Muhammad Saif-ur-Rehman
Tel.: 0208 / 88254806, email@example.com
Prof. Dr. Ioannis Iossifidis
Tel.: 0208 / 88254806, firstname.lastname@example.org