Browsing by Author "Ungen, Marc"
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- ItemDevelopment of a system to identify unmarked objects based on 3D-Object recognition and multi-sensor information(Stellenbosch : Stellenbosch University, 2021-03) Ungen, Marc; Louw, Louis; Palm, Daniel; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: Automatic identification (Auto-ID) technology serves as an interface between the real physical world and the virtual world of information by synchronising the physical flow of material with the virtual flow of information. Through this characteristic, Auto-ID technologies represent the core component for the implementation of the Internet of Things (IoT) in the context of Digitalisation and Industry 4.0. The Auto-ID technologies established over the years are almost exclusively based on the use of artificial identifiers for the purpose of identification, with barcodes and radio-frequency identification transponders being the most commonly used ones. In fact, the use of artificial identifiers causes additional effort, additional costs and is not even always applicable. By using the natural features of objects as identifiers, such drawbacks are avoided. Combining methods of 3D-Object recognition from the field of machine vision (MV) with further multi-sensor information and the data master from product data management, this thesis develops a novel multi-sensor Auto-ID system for the direct identification of unpackaged piece goods. Based on in-depth literature research, requirements for such a system are defined and transformed into a concept using engineering design methods. Subsequently, a first mechatronic prototype of the multi-sensor Auto-ID system is constructed and implemented, which includes both hardware and software development. The verification and functional test of the implemented system is then carried out by checking the prototype against the established requirements and by conducting a practical experiment. The results, based on the practically implemented prototype, show that reliable automatic identification of unmarked and unpackaged piece goods can be accomplished using multi-sensor information. This Auto-ID system prototype requires no artificial identifiers for the purpose of identification thus avoiding additional efforts, additional costs and issues with application.Furthermore, the use of multi-sensor information improves identification in terms of distinctiveness and accuracy, compared to purely optical instance-level 3D-Object recognition. This research contributes mainly to the existing scholarship in the field of Auto-ID technology. In particular, theoretical and practical contributions are made to the hitherto little-studied field of direct identification based on natural object features.