Date of Publication :19th August 2021

Abstract: In large warehouses, when conducting an inventory check or stock check, staff members are generally lifted up to high shelves utilizing a forklift, a truck, or scissor lift where they physically reach and examine/scan each standardized packet/item or box. This process is tedious, expensive, risky, and energy ineffective. To overcome this problem, we propose an autonomous drone-based technology using WhyCon Marker Localization System. Autonomous drones can navigate in storage areas very efficiently. They can scan and localize a maximum number of items/boxes on the go while sending live feedback of the stock inventory to the base station without any manual control. Generally, for autonomous drones, GPS based navigation system is used, but considering indoor warehouses GPS technology gives less accuracy for navigation. To counter this problem, we have used WhyCon Marker Localization System which uses a marker on a drone and an overhead camera to track the marker which in turn tracks the drone. This method is relatively inexpensive, can be implemented on lightweight drones, and gives high navigation accuracy in GPS denied environments as compared to other methods like SLAM, GPS, etc. For simulation and analysis, we have chosen an environment based on the Robot Operating System (ROS) and Gazebo simulator.

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