Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review

Background: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems be scattered and fragmented. Objective: This study seeks fill this research gap by using a systematic literature review approach. Methods: Based on data collected from Google Scholar, was performed, covering period 2016 2023. The driven protocol that comprehends inclusion exclusion criteria identify relevant papers. Results: Considering five categories have been identified: Deep Learning methods, probabilistic for solving Travelling-Salesman problem (TSP), algorithmic others. Specifically, performed analysis also provides community with an overview state-of-the-art which can further stimulate researchers practitioners enhance existing develop new ones in field.