A 3D object localization method based on EPNP and dual-view images

In many production fields such as chemical, food, fertilizers, cement, etc., products are usually shipped in bags and stacked on pallets in warehouses for sale and transportation. Currently, long-distance transportation mainly relies on semitrailer trucks or box trucks, while the loading and unloading process of bagged materials relies heavily on manpower and material resources, significantly reducing the overall efficiency of product logistics transportation. This paper proposes a 3D object localization method based on EPNP and dual-view images for addressing the stacking issues of goods in industries such as factory production and logistics transportation. The method employs two cameras and a gantry to form a goods stacking positioning detection system. The Zhang Zhengyou chessboard calibration method is utilized to calibrate the cameras and determine their intrinsic parameters. The three-dimensional coordinates of the goods are calculated through methods such as the EPNP algorithm, perspective projection principles, and coordinate transformations. Experimental results have shown that this method can accurately measure the position of goods under the camera, making it convenient for palletizing machines to accurately stack and improve palletizing efficiency.