Autonomous Inventory Tracking

Inventory management is a key part of the success of many businesses and organizations. Several methods to track inventory exist, the most common of which being manual tracking using items like hand scanners. However, manual input may be more prone to errors such as not scanning the item or double scanning. Some methods of autonomous tracking currently exist, however these are very large-scale and are expensive to produce and maintain. This project proposes a low-cost alternative for autonomous inventory tracking with a QR code-based inventory management robot utilizing a Raspberry Pi and Arduino. The robot uses a USB camera to detect product QR codes on a shelf while using several QTI sensors to follow a black line along the ground bordered at its edges to indicate the start and end point. On each run, the robot will move forward along the path, reversing when it detects the first border and finally stopping when it detects a second border. Meanwhile, as the robot moves along the path, the camera detects the QR codes along the shelves and records the data in a CSV format for easy exporting into databases and spreadsheet programs such as Excel. In practice, the robot functions in most rooms, even in those with lower lighting. Additionally, the robot can accurately and consistently read codes from a large range of distances, allowing for flexibility in its placement in a warehouse or store. Lastly, its cost-effectiveness allows for implementation in most businesses. Currently, more features are being implemented to improve the bot, including allowing it to read codes on higher shelves, improving camera quality and detection, researching alternatives to further reduce costs, and implementing a portable power solution for the Raspberry Pi.