@phdthesis{Philippczyk, type = {Bachelor Thesis}, author = {Yann Philippczyk}, title = {Implementing Deep Learning Object Recognition on NAO}, url = {https://nbn-resolving.org/urn:nbn:de:bsz:900-opus4-53948}, abstract = {Deep learning methods have proven highly effective for object recognition tasks, especially in the form of artificial neural networks. In this bachelor’s thesis, a way is shown to imple- ment a ready-to-use object recognition implementation on the NAO robotic platform using Convolutional Neural Networks based on pretrained models. Recognition of multiple objects at once is realized with the help of the Multibox algorithm. The implementation’s object recognition rates are evaluated and analyzed in several tests. Furthermore, the implementation offers a graphical user interface with several options to adjust the recognition process and for controlling movements of the robot’s head in order to easier acquire objects in the field of view. Additionally, a dialogue system for querying further results is presented.}, language = {en} }