Design and Development of an Automated Guided Vehicle (AGV) for Store and Warehouse Automation
Authors
Mr. Mayur Chavda
Mechatronics Engineering Dept., ITM Vocational University, Vadodara, Gujarat, India (IN)
Gadtya Paresh
UG Students, Mechatronics Engineering Dept., ITM Vocational University, Vadodara, Gujarat, India (IN)
Divyang Patel
UG Students, Mechatronics Engineering Dept., ITM Vocational University, Vadodara, Gujarat, India (IN)
Ms. Apexa Purohit
Mechatronics Engineering Dept., ITM Vocational University, Vadodara, Gujarat, India (IN)
Rajdeep Vatalia
UG Students, Mechatronics Engineering Dept., ITM Vocational University, Vadodara, Gujarat, India (IN)
Kushal Gajjar
UG Students, Mechatronics Engineering Dept., ITM Vocational University, Vadodara, Gujarat, India (IN)
Dr. Anil M. Bisen
Provost & Professor, Mechanical Engineering Dept., ITM Vocational University, Vadodara, Gujarat, India (IN)
Nayan Suthar
UG Students, Mechatronics Engineering Dept., ITM Vocational University, Vadodara, Gujarat, India (IN)
Dr. Mayank Dev Singh
Mechatronics Engineering Dept., ITM Vocational University, Vadodara, Gujarat, India (IN)
Article Information
DOI: 10.51583/IJLTEMAS.2025.1410000136
Subject Category: AGV
Volume/Issue: 14/10 | Page No: 1120-1127
Publication Timeline
Submitted: 2025-11-20
Published: 2025-11-20
Abstract
Abstract—The development of Automated Guided Vehicles (AGVs) has revolutionized material handling in industrial and commercial settings. This project focuses on designing, devel-oping, and testing a prototype AGV for store and warehouse automation. The AGV utilizes an ESP32 microcontroller, infrared (IR) sensors for line-following, and an ultrasonic sensor for obstacle detection. The vehicle is designed to follow a fixed path marked by a black line on the floor while avoiding obstacles in real-time. Built using cost-effective components, this prototype serves as a scalable and adaptable solution for educational and industrial applications. The system’s performance was validated through a series of controlled tests, demonstrating successful navigation, obstacle avoidance, and payload transport capabil-ities. The project aims to address the limitations of manual material handling, such as inefficiency, safety risks, and high labor costs, offering a reliable and cost-effective alternative for indoor logistics. Future enhancements could include dynamic navigation, wireless communication, and advanced control al-gorithms to further optimize the AGV’s performance in more complex environments.
Keywords
Automated Guided Vehicle (AGV), ESP32, Line Following, Obstacle Detection, Ultrasonic Sensor, Warehouse Automation, Robotics
This article is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Downloads
References
1. Zhiwei, X., et al., “Evolution and Improvement of AGVs in Industrial Automation,” Journal of Robotics and Automation, vol. 12, no. 2, pp. 45-56, 2021. [Google Scholar] [Crossref]
2. Zhang, J., et al., “Performance Evaluation of Line Following AGVs in Controlled Environments,” International Journal of Robotics, vol. 15, no. 3, pp. 120-130, 2019. [Google Scholar] [Crossref]
3. Li, F., et al., “Vision-Based Navigation for Autonomous Guided Vehi-cles,” Robotics and Autonomous Systems, vol. 22, no. 1, pp. 150-161, 2020. [Google Scholar] [Crossref]
4. Patel, R., et al., “Laser-Based Navigation for Autonomous Guided Vehicles in Complex Environments,” Journal of Intelligent Systems, vol. 19, pp. 35-48, 2018. [Google Scholar] [Crossref]
5. Wang, H., et al., “RFID-Based Navigation for AGVs in Dynamic Environments,” International Journal of Automation, vol. 10, pp. 202-214, 2021. [Google Scholar] [Crossref]
6. Xu, Y., et al., “Automation of Material Handling in Warehouses Using AGVs,” Warehouse Automation Journal, vol. 5, pp. 87-95, 2017. [Google Scholar] [Crossref]
7. Huang, C., et al., “Healthcare Logistics and the Role of Automated Guided Vehicles,” Journal of Healthcare Robotics, vol. 3, no. 2, pp. 66-74, 2020. [Google Scholar] [Crossref]
8. Jain, P., et al., “AGVs in Retail and E-Commerce: Trends and Applica-tions,” Retail Robotics Journal, vol. 6, pp. 101-112, 2021. [Google Scholar] [Crossref]
9. Liu, Z., et al., “Improving Navigation Accuracy for AGVs in Dynamic Environments,” Robotics Engineering Review, vol. 14, pp. 140-150, 2019. [Google Scholar] [Crossref]
10. Chen, J., et al., “Energy-Efficient AGV Systems and Power Management Techniques,” Energy Systems Journal, vol. 8, no. 4, pp. 90-98, 2018. [Google Scholar] [Crossref]
Metrics
Views & Downloads
Similar Articles
- Decision Tree and Automatic Linear Modeling Approaches to Predict Body Weight in Indigenous Sabi Sheep and Matebele Goat Females of Zimbabwe
- Microcontroller – Based Automatic Railway Crossing Control and Track Obstacle Monitoring System
- Modelling the Role of Absorptive Capacity in Foreign Direct Investment - Economic Growth Nexus: A Focus on South Africa’s Manufacturing Sector
- AI-Powered Wristband for Accurate BAC Monitoring Using Smart Data Fusion
- Climate Change Impacts on Different Regions