Recently, there has been a surge in the development of advanced warehouse management systems that seamlessly incorporate robotized technologies. These robots have the capability to operate independently or collaborate with human staff to enhance the efficiency of items picking and storage. The paper at hand, introduces an intelligent Warehouse Management System, denoted as iWMS, designed for a goods-to-person warehouse environment. The system is configured to retrieve data of standard format compatible with commercial WMS through an application programming interface (API), while maintaining control over the robotic processes. This work aims to address the development of a software that will analyze incoming and outgoing orders and allocate the task of collecting and distributing bins with an Autonomous Mobile Robot (AMR). The proposed software performs a systematic analysis of incoming orders, linking them with the respective fiducial markers that contain detailed information about the precise location of the relevant bin within the warehouse. Subsequently, the system assigns the task of orders collection to one or more AMRs, taking into account their availability and current positions within the warehouse. This is achieved using an algorithm that maximizes efficiency by optimizing both execution time and travel distances. Additionally, the application consistently updates the stock in the database based on the products identified within the bins, ensuring accurate and real-time stock counting in the warehouse database. The ultimate goal of the iWMS is to provide an easy-to-use tool, allowing the seamless co-existence between the workers and the robotic platforms in a common workplace. This iWMS is part of a robotic warehouse solution currently undergoing testing in simulation.