A Review on Computer based Mobile Robotics for Automated Ma-terial Handling in Large Scale Warehouse

In recent years, the use of autonomous mobile robots in warehouses has increase better generalization to new objects and environments than RT-1ased rapidly due to the growing demand for fast and accurate inventory management. One of the major challenges faced by these robots is detecting and identifying items placed on shelves, especially in cluttered and dynamic environments. This paper proposes a mobile robot system that uses computer vision techniques to detect items in a warehouse setting. The system uses a camera mounted on the robot along with deep learning-based object detection model to identify items in real time while the robot moves through the warehouse. The main aim of this project is to reduce human effort in inventory checking and item picking by allowing the robot to automatically detect and locate ims. The paper also discusses the difficulties faced during implementation, such as poor lighting conditions, occlusion of items and the need for fast processing on limited hardware. This paper proposes a conceptual framework. Implementation and empirical validation of detection accuracy and processing speed are identified as necessary next steps. This work shows that computer vision-based robots can be a useful solution for improving efficiency in warehouse operations and reducing manual work.