Design and Implementation of an Autonomous Smart Food Delivery Robot for Commercial Environments

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Design and Implementation of an Autonomous Smart Food Delivery Robot for Commercial Environments

Author Information
1
Department of Mechanical Engineering, Palestine Technical University—Kadoorie, Tulkarm P.O. Box 7, Palestine
2
Department of Computer Science, Palestine Technical University—Kadoorie, Tulkarm P.O. Box 7, Palestine
*
Authors to whom correspondence should be addressed.

Received: 29 August 2025 Revised: 23 September 2025 Accepted: 10 December 2025 Published: 16 December 2025

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© 2025 The authors. This is an open access article under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

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Intell. Sustain. Manuf. 2026, 3(1), 10034; DOI: 10.70322/ism.2025.10034
ABSTRACT: The integration of robotics into service environments is transforming how labor-intensive tasks are managed, particularly during peak hours with staff shortages and long wait times. This research presents a fully autonomous, modular food-delivery robot designed to enhance operational efficiency and improve service experience. The system combines artificial intelligence, facial recognition, smartphone-based order management, Arduino, ESP32, ESP32-CAM, and Python to navigate indoor environments and deliver food directly to recipients, supported by a secure handover mechanism. Experimental results indicate that the robot performs waiter-like delivery reliably, maintaining mobility and structural integrity across various surfaces by using lightweight materials and motors that have been optimized. Through the use of a motion coordination algorithm, responsive navigation can be achieved, while a simple user interface can be operated by anyone with minimal training. According to these results, automation reduces the need for manual labor, increases the speed of service, and ensures consistency in the delivery process. Additionally, the system provides a practical framework for future research and potential applications beyond food delivery, such as surveillance, environmental monitoring, and disaster response. Future work will focus on scaling for real-world deployment and integration advanced AI navigation to enhance autonomy, adaptability, and overall operational performance.
Keywords: Autonomous robotics; Food delivery system; Artificial intelligence; Service automation; Indoor navigation

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