Copyright © 2026 Authors retain the copyright of this article. This article 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.

@article{200919,
        author = {Atharva D Shingare and Dr. Anjali J Joshi and Dr. Bhuvaneshwar D Patil and Mr. Mayuresh B Shinde},
        title = {Literature Review on Vision-Based Autonomous Robot for Godown Material Management},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {2201-2216},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200919},
        abstract = {This study presents the design and implementation of a vision-based autonomous robot for efficient material management in godown environments. Leveraging advanced computer vision, simultaneous localization and mapping (SLAM), and autonomous navigation techniques, the proposed system aims to automate inventory tracking, order fulfillment, and material handling tasks. The robot integrates high-resolution cameras, LiDAR sensors, and deep learning-based perception algorithms to achieve accurate object recognition and real-time environment mapping. Experimental evaluation demonstrates significant improvements in operational efficiency and accuracy, highlighting the potential for large-scale deployment in warehouse and storage facilities.
The growing demand for real-time inventory visibility in warehouses and godowns has led to the development of vision-based autonomous mobile robots (AMRs). These robots can navigate complex warehouse layouts without pre-installed guidance systems. The system comprises modules such as data acquisition, perception, localization and mapping, path planning, control and navigation, manipulation, and WMS integration. Experimental trials show that vision-based AMRs can significantly enhance material management efficiency, reduce manual intervention, and maintain high accuracy in inventory tracking. Integration with WMS enables seamless synchronization of physical operations and digital records. The system is expected to streamline godown operations, improve inventory accuracy, enhance safety, and provide scalable solutions adaptable to different warehouse sizes and configurations. Future work will focus on multi-robot coordination, edge AI optimization, and full-scale industrial deployment.},
        keywords = {Autonomous Mobile Robot; Computer Vision; SLAM; Path Planning; Material Handling; Material Management System},
        month = {May},
        }