Furniture board segmentation based on multiple sensors and integer programming model

Abstract:

In the current furniture production line, the level of automation in the stage of loading and unloading is not high enough. In order to improve its automation, a novel integer programming based method for automatically segmenting board is proposed and a multi-sensor configuration is given. In such a configuration, we include multiple cameras and Lidar sensors. The cameras attached on each board are used to collect quick response (QR) code information, while Lidar sensors can obtain each board's contours information. We then formulate each board's segmentation as the integer programming problem. The experimental results show that our method can achieve a very high segmentation accuracy of 95% on average.