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  • Pallets Detection and position tracking for automated guided vehicles

Pallets Detection and position tracking for automated guided vehicles

Posted on January 20, 2022January 20, 2022 By Muhammad Saif-Ur-Rehman
teaching

Bachelorarbeitsthema

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

  1. Literature review and programming language background (30 days)
  2. 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”.
  3. 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.
  4. Program a Graphical user interface (GUI) (30days)Lastly, for the successful completion of the Master thesis a professional GUI with embedded solution is required.
  5. Writing Master thesis (60 days)Writing a master thesis report in English or German.

Prerequisites:

  • 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

Co-supervisors:

Dr. Ing. Muhammad Saif-ur-Rehman
Tel.: 0208 / 88254806, muhammad.saif-ur-rehman@hs-ruhrwest.de 

Supervisors:
Prof. Dr. Ioannis Iossifidis
Tel.: 0208 / 88254806, iossifidis@hs-ruhrwest.de

Tags: thesis

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