Localization of Humans in Warehouse based on Rack Detection

Abstract

This paper proposes a method for human localization in the automated warehouses. As the environment is highly dynamic due to changes in the racks content as well as the position of the rack, the proposed method uses the racks as landmarks for the localization. The fixed structure of the shelves and stands of the rack is used to detect the rack itself regardless of the content. The structure is coded as the graph and the detection is performed by finding the isomorphism between the rack model and the detected structure of the environment. The relative position is obtained by solving a PnP problem. The global position of the rack is gathered from the warehouse system by reading the marker identifying the rack. Experiments show that the localization has a mean error of 15 cm and is much more robust than the localization based on the marker itself.

Safe Interaction of Automated Forklifts and Humans at Blind Corners in a Warehouse with Infrastructure Sensors

“…By including support from infrastructure and infrastructure-based sensors, these problems can be avoided. For example, humans could be located in a warehouse using camera-data [14] or ultra wide band (UWB) technology [25,32] with a precision of at least 15 cm. Further, such a real-time locating system (RTLS) can also be used to predict the paths of workers [15].…”