Enhancing human–robot collaboration with thermal images and deep neural networks: the unique thermal industrial dataset WLRI-HRC and evaluation of convolutional neural networks

Süme, Sinan; Ponomarjova, Katrin-Misel; Wendt, Thomas M.; Rupitsch, Stefan J.

doi:https://doi.org/10.5194/jsss-14-37-2025

Articles | Volume 14, issue 1

https://doi.org/10.5194/jsss-14-37-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Sensors and Measurement Systems 2024

https://doi.org/10.5194/jsss-14-37-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 1

Regular research article

|

18 Feb 2025

Regular research article |

| 18 Feb 2025

Enhancing human–robot collaboration with thermal images and deep neural networks: the unique thermal industrial dataset WLRI-HRC and evaluation of convolutional neural networks

Sinan Süme, Katrin-Misel Ponomarjova, Thomas M. Wendt, and Stefan J. Rupitsch

Data sets

``WLRI-HRC'' -- A Dataset of Infrared Images for Human-Robot Collaboration in Manufacturing Environment S. Süme https://doi.org/10.5281/zenodo.14228565

Short summary

This contribution deals with the exploration of human–robot collaboration using an infrared sensor and artificial intelligence (AI) to improve the safety and efficiency of the collaboration. The main contribution is the unique thermal dataset WLRI-HRC generated in a manufacturing environment and the evaluation of the dataset using different AI network methods.