@inproceedings{6539a59838e0479eb768780fa3a26426,
title = "Real-time Pallet Localization with 3D Camera Technology for Forklifts in Logistic Environments",
abstract = "This paper presents a novel approach for detection and localization of standardized euro pallets, which are orientated up to 90° in relation to the sensor plane. There is no a priori information about the pallets pose needed. We use a time-of-flight camera. Our algorithm is based on finding surfaces in the point cloud, which represent the three wooden blocks of a euro pallet. Different kinds of geometrical checks set up our detection pipeline, where no artificial markers on the pallets are needed. Since we perform the detection while driving a forklift, the algorithm must process the point cloud within a set time limit. The detection and localization result in the pallets position and orientation in relation to the camera coordinate system. This information can be provided to higher-level systems, like advanced driver assistance systems. The results show that the localization of pallets is possible in the scenario considered.",
keywords = "Kinect camera, forklift, pallet detection, pallet localization, point cloud, time-of-flight camera",
author = "Benjamin Molter and Johannes Fottner",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2018 ; Conference date: 31-07-2018 Through 02-08-2018",
year = "2018",
month = sep,
day = "28",
doi = "10.1109/SOLI.2018.8476740",
language = "English",
series = "Proceedings of the 2018 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "297--302",
booktitle = "Proceedings of the 2018 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2018",
}