Pallet Detection Based on Halcon and AlexNet Network for Autonomous Forklifts

Abstract

Pallet detection is the key step of cargo handling for autonomous forklifts. Due to the influence of complex background, the recognition rate of pallet detection is low. In order to improve the recognition rate, a pallet detection method based on point cloud is proposed. In this method, time-of-flight (ToF) camera is used to collect the point cloud. AlexNet network which is provided by Halcon software is used for deep learning, and deep learning is used to extract the region of interest of pallet contour. The extracted region of interest is processed to obtain the regions of the pallet contour, and the pallet center is solved. The experimental results show that the precision of pallet detection can reach 92.0%. This method has high recognition rate in complex background, and has reference value for the design of pallet detection system of autonomous forklifts.