Map Partition Method for Warehouse Logistics Management with Physical Robot Application

The increasing complexity of industrial warehouse environments demands advanced spatial decomposition methods to enhance robotic logistics operations. This paper presents an map segmentation framework designed to address structural heterogeneity in modern storage facilities. The proposed methodology integrates multi-scale edge detection with dynamic morphological processing, employing gradient-based feature extraction and probabilistic line detection to accurately identify architectural elements. By coupling spatial partitioning with navigation requirements, the framework implements intelligent zoning strategies that optimize pathfinding efficiency while maintaining robustness against environmental variability. Experimental validation through physical robotic deployments in operational warehouses demonstrates the system’s effectiveness in diverse architectural configurations and dynamic obstacle scenarios.