TY  - CPAPER
U1  - Konferenzveröffentlichung
A1  - Wendt, Thomas
A1  - Süme, Sinan
A1  - Amal, Kaithavalappil Ajay
T1  - A New and Innovative Approach to Recognizing a Machine Based on the Structural Fingerprint: Instance Segmentation and Distance Measuring with a Single RGB-D Camera
T2  - ICCR 2024 : 2024 6th International Conference on Control and Robotics
N2  - In this paper an approach to enable mobile robots to localize and position correctly on special machines based on their unique fingerprint in manufacturing is introduced. This is achieved using a single RGB-D camera and the use of Convolutional Neural Networks, i.e. Mask-RCNN. The utilized network is trained on the individual shape of the machine to recognize, classify, and segment it, so the mobile robot can locate the correct machine without any further modifications to the machine. Additionally, the depth information of the identified object is processed to calculate the distance to the machine. For this, real data of special machines were taken, labeled and the Mask-RCNN model was trained. This approach shows promising results, with average values of the Jaccard Index at 95.9 % and the Dice Coefficient at 97.7 %, and an inference time of 0.083 s, enabling real-time detection.
KW  - AI
KW  - Computer Vision
KW  - Robotik
KW  - Instance Segmentation
KW  - Künstliche Intelligenz
Y1  - 2025
SN  - 979-8-3315-1814-1 (USB)
SB  - 979-8-3315-1814-1 (USB)
SN  - 979-8-3315-1815-8 (Elektronisch)
SB  - 979-8-3315-1815-8 (Elektronisch)
SN  - 979-8-3315-1816-5 (Print on Demand)
SB  - 979-8-3315-1816-5 (Print on Demand)
U6  - https://doi.org/10.1109/ICCR64365.2024.10927456
DO  - https://doi.org/10.1109/ICCR64365.2024.10927456
SP  - 259
EP  - 264
PB  - IEEE
ER  -