There is a continuing trend in the aircraft industry to automate production. In order to be able to react to shortages of skilled workers, high order fluctuations and machine breakdowns, cost-effective, mobile and flexible systems are required to support the workers. This paper focuses on the integration of existing skill-based engineering concepts into production using standard OPC Unified Architecture interface, where production systems can be built quickly by simply interconnecting modules. The interconnected modules together form higher level subsystems enabling reusability of the individual modules as well as the assembled subsystems across several use cases. The approach is evaluated on a production related mobile robot system, whose task is to drive to the workstation, reference the component and drill holes in a vertical tail plane section of an aircraft. All devices from different suppliers contain skill-based modules based on standards defined by OPC Foundation and communicate via OPC UA-based Client/Server communication.
The concept of building 3D models, known as 3D reconstruction, already exists since the last few decades. However, by manually aligning the objects during acquisition phase does not guarantee that the output, the 3D models, will be perfectly aligned with the computer's world coordinate system. It mainly happens because in real world it is quite challenging to get perfect measurements, especially for the irregular objects. In this paper we address this problem by proposing a method to be used on the post processing phase of the 3D reconstruction process. The method is based on the variance and symmetricity of the object's point cloud which is acquired during acquisition. For the evaluation, we applied and evaluated the proposed method to both synthetic and reconstructed 3D models. The results are significant and show that the method capable of aligning the models to a fine resolution of 1' (one minute) angle.
The concept of building 3D models, known as 3D reconstruction, already exists since the last few decades. However, by manually aligning the objects during acquisition phase does not guarantee that the output, the 3D models, will be perfectly aligned with the computer's world coordinate system. It mainly happens because in real world it is quite challenging to get perfect measurements, especially for the irregular objects. In this paper we address this problem by proposing a method to be used on the post processing phase of the 3D reconstruction process. The method is based on the variance and symmetricity of the object's point cloud which is acquired during acquisition. For the evaluation, we applied and evaluated the proposed method to both synthetic and reconstructed 3D models. The results are significant and show that the method capable of aligning the models to a fine resolution of 1' (one minute) angle.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.