Real Time Volume Measurement of Logistics Cartons Through 3D Point Cloud Segmentation

Vision-based measurement has been studied extensively in recent decades for its potential applications in robotics. However, there still remain challenges when we aim at a fast and robust detecting system even in the presence of damaged cartons. This paper implements a non-contact volume measurement system based on point cloud geometric properties of objects for logistics parcels, which recognizes and measures different types of objects or even deformed cartons in various scenarios. Our proposed method is robust to handle the different sizes of objects using the same system. Experimental verification is performed with different cartons on the conveyor belt, results indicate that our proposed system with error percentage in volume is 5.92% with an affordable 3D camera (ASUS Xtion Pro Live).