Utilizing Cloud Solutions for Object Recognition in the Context of Industrial Robotics Sorting Tasks

The rapid advancements in sectors such as Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), networking and cloud computing are opening the opportunity for integrating these techniques with robots from the manufacturing field, with the promising perspective of improved performance at reduced costs, inspiring the new field of cloud robotics. In this paper, we propose an architecture for integrating industrial robots with Cloud AI object recognition services. For our proposed solution, we explore the results obtained by simulating a sorting task in RobotStudio, communicating with Microsoft Azure Custom Vision API by sending the web service calls from a computer running a Python script. We present the cycle time added by the communication with the cloud service and test the robustness of the system by comparing the results obtained with four sets of images: unaltered, altered with gaussian noise, barrel distortion and both.

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Publication Details

Published
2024-09-04
DOI
https://doi.org/10.1109/inista62901.2024.10683834
Citations
1
Primary Topic
Wireless Sensor Networks for Data Analysis
Type
article
Field-Weighted Citation Impact
0.35
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article

Utilizing Cloud Solutions for Object Recognition in the Context of Industrial Robotics Sorting Tasks

D. Popescu, Andrei Mateescu, Ioan Ştefan Sacală, Ioana Miruna Vlasceanu et al.
1 citations
Wireless Sensor Networks for Data Analysis
0.35
article

Utilizing Cloud Solutions for Object Recognition in the Context of Industrial Robotics Sorting Tasks

D. Popescu, Andrei Mateescu, Ioan Ştefan Sacală, Ioana Miruna Vlasceanu, Ioana Livia Stefan
article en
1 citations

Abstract

The rapid advancements in sectors such as Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), networking and cloud computing are opening the opportunity for integrating these techniques with robots from the manufacturing field, with the promising perspective of improved performance at reduced costs, inspiring the new field of cloud robotics. In this paper, we propose an architecture for integrating industrial robots with Cloud AI object recognition services. For our proposed solution, we explore the results obtained by simulating a sorting task in RobotStudio, communicating with Microsoft Azure Custom Vision API by sending the web service calls from a computer running a Python script. We present the cycle time added by the communication with the cloud service and test the robustness of the system by comparing the results obtained with four sets of images: unaltered, altered with gaussian noise, barrel distortion and both.

Universitatea Națională de Știință și Tehnologie Politehnica București (RO)
Decent work and economic growth
Openalex Percentile: Top 39%
Wireless Sensor Networks for Data Analysis
0.35
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