TY - CPAPER U1 - Konferenzveröffentlichung A1 - Ungen, Marc A1 - Louw, Louis A1 - Palm, Daniel T1 - Multi-sensor identification of unmarked piece goods T2 - Proceedings of the 2nd Conference on Production Systems and Logistics : CPSL 2021, 25-28 May 2021, Vancouver, Canada N2 - The seamless fusion of the virtual world of information with the real physical world of things is considered the key for mastering the increasing complexity of production networks in the context of Industry 4.0. This fusion, widely referred to as the Internet of Things (IoT), is primarily enabled through the use of automatic identification (Auto-ID) technologies as an interface between the two worlds. Existing Auto-ID technologies almost exclusively rely on artificial features or identifiers that are attached to an object for the sole purpose of identification. In fact, using artificial features for the purpose of identification causes additional efforts and is not even always applicable. This paper, therefore, follows an approach of using multiple natural object features defined by the technical product information from computer-aided design (CAD) models for direct identification. By extending optical instance-level 3D-Object recognition by means of additional non-optical sensors, a multi-sensor automatic identification system (AIS) is realised, capable of identifying unpackaged piece goods without the need for artificial identifiers. While the implementation of a prototype confirms the feasibility of the approach, first experiments show improved accuracy and distinctiveness in identification compared to optical instance-level 3D-Object recognition. This paper aims to introduce the concept of multisensor identification and to present the prototype multi-sensor AIS. KW - natural identifiers KW - multi-sensor identification KW - 3D-object recognition KW - automatic identification KW - direct identification KW - computer-aided design (CAD) Y1 - 2021 UN - https://nbn-resolving.org/urn:nbn:de:bsz:rt2-opus4-32896 SN - 2701-6277 SS - 2701-6277 U6 - https://doi.org/10.15488/11236 DO - https://doi.org/10.15488/11236 SP - 740 EP - 748 S1 - 9 PB - Leibniz-Universität Hannover CY - Hannover ER -