“Plug-and-Play” Inventory Robots: Autonomous Itinerary Planning Through Autonomous Waypoint Generation

Current robotic inventory systems rely on human interaction for installation, configuration, and reconfiguration tasks. However, this dependence on human involvement hampers the efficiency of the process chain in the industry and can lead to bottlenecks in the supply chain and the overall system. In this study, we present a “plug-and-play” methodology that enables the deployment of inventory robots and the autonomous reconfiguration of the map and inventory itineraries. This work introduces, for the first time, an autonomous waypoint generation method based on radiofrequency identification exploration and the first fully autonomous solution for designing efficient itineraries for inventory robots. The proposed methodology is extensively detailed, and a series of experiments are conducted in a real environment with physical robots. The results demonstrate that the autonomously designed inventory itineraries achieved through the proposed method exhibit similar performances to those designed by humans.