ORIGINAL RESEARCH article
Front. Robot. AI
Sec. Industrial Robotics and Automation
Volume 12 - 2025 | doi: 10.3389/frobt.2025.1603729
Robotic Optimization of Powdered Beverages Leveraging Computer Vision and Bayesian Optimization
Provisionally accepted
- 1ETH Zürich, Zurich, Zürich, Switzerland
- 2Swiss Federal Institute of Technology Lausanne, Lausanne, Vaud, Switzerland
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The growing demand for innovative research in the food industry is driving the adoption of robots in large-scale experimentation, a shift that offers increased precision, repeatability, and efficiency in product manufacturing and evaluation. This paper addresses this need by introducing a robotic system that extends automation into optimization and closed-loop quality control, using powdered cappuccino preparation as a case study. By leveraging Bayesian Optimization and image analysis, the robot explores the parameter space to identify the ideal conditions for producing cappuccino with high foam quality. A computer vision-based feedback loop further improves the beverage by mimicking human-like corrections in preparation process. Findings demonstrate the effectiveness of robotic automation in achieving high repeatability and enabling extensive exploration of system parameters, paving the way for more advanced and reliable food product development.
Keywords: Bayesian optimization, Computer Vision, Robotics, Food Analysis, food optimization
Received: 31 Mar 2025; Accepted: 21 May 2025.
Copyright: © 2025 Szymanska and Hughes. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Josie Hughes, Swiss Federal Institute of Technology Lausanne, Lausanne, 1015, Vaud, Switzerland
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.