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Karan R. Wadalkar,
Prasad V. Salunke,
Pratik S. Satalkar,
Sayli J. Tambe,
Abhinandan Kondekar,
Naveen Kumar,
- Student, Mechatronics Engineering Department, Sanjivani College of Engineering, Kopargaon, Maharashtra, India
- Student, Mechatronics Engineering Department, Sanjivani College of Engineering, Kopargaon, Maharastra, India
- Student, Mechatronics Engineering Department, Sanjivani College of Engineering, Kopargaon, Maharastra, India
- Student, Mechatronics Engineering [email protected], Sanjivani College of Engineering, Kopargaon, Maharastra, India
- Student, Mechatronics Engineering [email protected], Sanjivani College of Engineering, Kopargaon, Maharastra, India
- Student, Mechatronics Engineering [email protected], Sanjivani College of Engineering, Kopargaon, Maharastra, India
Abstract
This project is the development of an Automated Guided Vehicle (AGV) system that has been developed to handle materials in the high-accuracy, reliability, and efficiency in industrial settings. The AGV is a combination of a blend of advanced technologies including sensor fusion, real-time path planning, and AI-based navigation to allow smooth and intelligent operation with minimal human intervention. The vehicle is able to efficiently identify, and evade obstacles by using a combination of sensors, such as RADAR sensors, computer vision systems and dynamically plan the most optimal routes in changing and uncertain environments. A hybrid control approach is adopted to increase adaptability and performance, which involves machine learning algorithms with a rule-based motion planning. This will enable the AGV to react intelligently to real time conditions and still retain stability and precision in its movements. The Internet of Things (IoT) capabilities further enhance the system by providing the possibility of remote monitoring, the ability to schedule preventative maintenance and the ability to centrally manage multiple AGVs in a networked industrial environment. The proposed system has several advantages in that it enhances speed in transportation of material, decreases reliance on human labor, minimizes human error, and lowers operational costs. It is especially useful in the manufacturing and warehouse setting where efficiency and consistency are very important. As experimental evidence shows, the developed AGV is capable of successfully carrying the payloads of up to 4 kg along the predetermined routes and maintaining the stable and reliable performance. It also displays good obstacle detection and avoidance systems as well as easy navigation during various surface conditions. The strength, adaptability, and scalability of the system has made it a prospective solution to the modern automated material handling programs.
Keywords: Automated Guided Vehicle, Navigation, Sensor Integration, Industrial Automation, IoT, Smart Logistics, Motion Planning.
Karan R. Wadalkar, Prasad V. Salunke, Pratik S. Satalkar, Sayli J. Tambe, Abhinandan Kondekar, Naveen Kumar. Intelligent Automated Guided Vehicle (AGV) System for Optimized Material Handling. Trends in Mechanical Engineering & Technology. 2026; 16(02):-.
Karan R. Wadalkar, Prasad V. Salunke, Pratik S. Satalkar, Sayli J. Tambe, Abhinandan Kondekar, Naveen Kumar. Intelligent Automated Guided Vehicle (AGV) System for Optimized Material Handling. Trends in Mechanical Engineering & Technology. 2026; 16(02):-. Available from: https://journals.stmjournals.com/tmet/article=2026/view=247980
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Trends in Mechanical Engineering & Technology
| Volume | 16 |
| 02 | |
| Received | 13/01/2026 |
| Accepted | 09/04/2026 |
| Published | 13/06/2026 |
| Publication Time | 151 Days |
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