Design and Development of an Autonomous Cafeteria Robot for Food Delivery using RFID-Based Order Verification

Abstract

The rapid expansion of the foodservice robotics market, valued at USD 2.4 billion in 2024 and projected to reach USD 7.3 billion by 2030, has created significant opportunities for automation ininstitutionaldiningenvironments. Ourprojectaddressesthecriticalneedforautonomousfood delivery systems in cafeterias through the development of a sophisticated robot that combines precisenavigation, secureauthentication,andreliablemechanicaldesign.Thesystemachieves remarkable positioning accuracy of ±8.2 cm and maintains a 99.8% authentication success rate while supporting 8 kg payload capacity with over 6 hours of autonomous operation. Our autonomous cafeteria robot integrates differential-drive locomotion with high-precision odometry, encrypted RFID authentication, and a distributed multi-microcontroller architecture. The navigation system employs advanced algorithms including D* Lite-based path replanning capable of sub-30 ms response times, while security is ensured through an AES-128/CBC encryptedRFIDprotocolwithrollinginitializationvectors.Therobotsuccessfullycompletedover 200 test delivery cycles with 100% completion rate, demonstrating its readiness for real-world cafeteria deployment.

Introduction

The project addresses significant challenges in institutional cafeteria automation, where existing robotic systems suffer from navigation errors, network latency, and unreliable authentication, leading to high waste and mis-delivery rates. The team developed an autonomous cafeteria robot featuring advanced navigation, secure RFID-based authentication, and a robust system architecture designed for dynamic, indoor environments.

Key innovations include a three-tier computational setup using an NVIDIA Jetson Nano with specialized microcontrollers for precise motor control and user interaction, high-resolution encoders for accurate positioning, and a secure authentication protocol employing AES encryption to ensure food delivery accuracy.

Extensive testing demonstrated the robot’s superior navigation accuracy (8.2 cm positioning error), reliability in authentication (99.8% success rate), and endurance over multiple delivery cycles. The system also handles payloads up to 8 kg efficiently, with robust power management and communication protocols optimized for cafeteria conditions.

Future enhancements proposed include dynamic obstacle detection with RGB-D or LiDAR sensors, multi-robot fleet coordination via cloud-based MQTT, and autonomous charging to enable continuous operation. The modular design supports maintainability and integration of future technologies, making it a practical and scalable solution for automated food delivery in institutional dining.

Conclusion

The autonomous cafeteria robot developed through our project represents a significant advancement in service robotics, successfully addressing the critical challenges of precise navigation,secureauthentication,andreliableoperationindynamicindoorenvironments.Our innovative combination of differential-drive locomotion, encrypted RFID authentication, and distributedcontrolarchitecturehasproducedasystemthatconsistentlyexceedsperformance specifications while maintaining the robustness required for commercial deployment. Thequantitativevalidationofourdesignthroughextensivetestingdemonstratespositioning accuracy of 8.2 cm, authentication success rates of 99.8%, and 100% delivery completion across 200+ operational cycles. These results confirm that our robot is ready for real-world cafeteria deployment and provides a solid foundation for future enhancements including dynamic obstacle avoidance, fleet coordination, and autonomous charging capabilities. Ourprojectcontributesvaluableinsightstothefieldofservicerobotics,particularlyintheareas of secure authentication protocols, precision navigation in constrained environments, and distributed control system architectures. The successful integration of these technologies in a practical, deployable system demonstrates the potential for robotics to transform institutional dining operations while improving efficiency, accuracy, and safety. The experience gained through this development project has prepared our team for advanced research in autonomous systems and provided practical insights into the challenges of transitioninglaboratoryroboticsresearchintoreal-worldapplications. Themodular,maintainable design we have created ensures that future improvements can be integrated seamlessly, supporting the continued evolution of cafeteria automation technology.

References

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Copyright

Copyright © 2025 Aayush Singh, Ayush Ganesh Salian , Keyuri Shanbhag , Mohit Chikkadi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.