Indoor Mapping and Reconstruction with Mobile Augmented Reality Sensor Systems

Augmented Reality (AR) ermöglicht es, virtuelle, dreidimensionale Inhalte direkt innerhalb der realen Umgebung darzustellen. Anstatt jedoch beliebige virtuelle Objekte an einem willkürlichen Ort anzuzeigen, kann AR Technologie auch genutzt werden, um Geodaten in situ an jenem Ort darzustellen, auf den sich die Daten beziehen. Damit eröffnet AR die Möglichkeit, die reale Welt durch virtuelle, ortbezogene Informationen anzureichern. Im Rahmen der vorliegenen Arbeit wird diese Spielart von AR als "Fused Reality" definiert und eingehend diskutiert. Der praktische Mehrwert, den dieses Konzept der Fused Reality bietet, lässt sich gut am Beispiel seiner Anwendung im Zusammenhang mit digitalen Gebäudemodellen demonstrieren, wo sich gebäudespezifische Informationen - beispielsweise der Verlauf von Leitungen und Kabeln innerhalb der Wände - lagegerecht am realen Objekt darstellen lassen. Um das skizzierte Konzept einer Indoor Fused Reality Anwendung realisieren zu können, müssen einige grundlegende Bedingungen erfüllt sein. So kann ein bestimmtes Gebäude nur dann mit ortsbezogenen Informationen augmentiert werden, wenn von diesem Gebäude ein digitales Modell verfügbar ist. Zwar werden größere Bauprojekt heutzutage oft unter Zuhilfename von Building Information Modelling (BIM) geplant und durchgeführt, sodass ein digitales Modell direkt zusammen mit dem realen Gebäude ensteht, jedoch sind im Falle älterer Bestandsgebäude digitale Modelle meist nicht verfügbar. Ein digitales Modell eines bestehenden Gebäudes manuell zu erstellen, ist zwar möglich, jedoch mit großem Aufwand verbunden. Ist ein passendes Gebäudemodell vorhanden, muss ein AR Gerät außerdem in der Lage sein, die eigene Position und Orientierung im Gebäude relativ zu diesem Modell bestimmen zu können, um Augmentierungen lagegerecht anzeigen zu können. Im Rahmen dieser Arbeit werden diverse Aspekte der angesprochenen Problematik untersucht und diskutiert. Dabei werden zunächst verschiedene Möglichkeiten diskutiert, Indoor-Gebäudegeometrie mittels Sensorsystemen zu erfassen. Anschließend wird eine Untersuchung präsentiert, inwiefern moderne AR Geräte, die in der Regel ebenfalls über eine Vielzahl an Sensoren verfügen, ebenfalls geeignet sind, als Indoor-Mapping-Systeme eingesetzt zu werden. Die resultierenden Indoor Mapping Datensätze können daraufhin genutzt werden, um automatisiert Gebäudemodelle zu rekonstruieren. Zu diesem Zweck wird ein automatisiertes, voxel-basiertes Indoor-Rekonstruktionsverfahren vorgestellt. Dieses wird außerdem auf der Grundlage vierer zu diesem Zweck erfasster Datensätze mit zugehörigen Referenzdaten quantitativ evaluiert. Desweiteren werden verschiedene Möglichkeiten diskutiert, mobile AR Geräte innerhalb eines Gebäudes und des zugehörigen Gebäudemodells zu lokalisieren. In diesem Kontext wird außerdem auch die Evaluierung einer Marker-basierten Indoor-Lokalisierungsmethode präsentiert. Abschließend wird zudem ein neuer Ansatz, Indoor-Mapping Datensätze an den Achsen des Koordinatensystems auszurichten, vorgestellt

Enhancing Decision-Making In SCM: Investigating The Status Quo And Obstacles Of Advanced Analytics In Austrian Companies

Over the past few years, the stability and predictability of logistics and supply chain networks have significantly decreased. This has led to higher risks and increased uncertainty in decision-making within supply chain management (SCM). Fortunately, the abundance of available data presents a tremendous opportunity to alleviate this uncertainty. However, realizing the full potential of advanced analytics, such as predictive and prescriptive analytics, is hindered by a lack of knowledge regarding their practical applications and performance benefits, as well as a deficiency in implementation expertise. This research paper examines the current state of advanced analytics applications and the primary challenges faced by Austrian companies in this domain. The findings reveal a distinct pattern: although the literature highlights numerous performance advantages, the practical utilization of advanced analytics remains at a rudimentary stage and is primarily confined to isolated departments. While demand management, procurement, and transport planning have shown some initial success in their implementation, other areas like production planning and, particularly, warehouse management lag. The primary challenges observed in practice include a limited understanding of the potential of advanced analytics, lack of transparency and data quality issues, difficulties in internal marketing, and inadequate organizational integration. These challenges, along with potential courses of action, serve as a starting point for other companies aiming to address similar issues. The significance of this work lies not only in its theoretical contribution to existing research on advanced analytics in SCM but also as one of the few studies that delve into the practical implementation and specific application domains of advanced analytics in Austria

The Contribution of new Production Technologies and Circular Economy Towards meeting the Future Demand of Proton-exchange Membrane Fuel Cells – A Literature Review

The energy and mobility sectors contribute significantly towards the global CO2 emissions. The proton-exchange membrane fuel cell finds application in both sectors and represents a possible green and sustainable technology for electricity generation. Current production rates do not satisfy the predicted demand for proton-exchange membrane fuel cells as the diffusion of this technology keeps increasing. Nor does the per-part cost guarantee a globally sufficiently broad application. The industry must overcome technological and economic obstacles to enable higher production rates at a lower cost per unit. This research gives an overview of current proton-exchange membrane fuel cell production and stacking technologies and provides an outlook on processes that need to be improved to enable faster and lower-cost production. Additionally, the impact of remanufacturing as an end of life option on the circular economy, production, and ecological impact of proton-exchange membrane fuel cells is examined. The knowledge generated by this research shall support increasing proton-exchange membrane fuel cell production rates to catch up with the predicted demand. Since current research on proton-exchange membrane fuel cell remanufacturing is rare, findings on this topic will support the industry in preparing for circular production processes in the future. Results of the present work include an overview of the current state of production for proton-exchange membrane fuel cells, the areas that need improvement, and the role of a circular economy

Impact of Bimodal Particle Size Distribution Ratio of Functional Calcium Carbonate Filler on Thermal and Flowability Properties of Polyamide 12

In previous investigations, it was shown that the melting, as well as crystallization behavior of polyamide 12, could be manipulated by adjusting the particle size distribution of calcium carbonate as a functional filler. It was demonstrated that the melt properties of this compound show a significant dependency on the filler volume-based particle size. As finer and narrower the calcium carbonate particles in the polymer matrix become, the less influence the filler has on the melting properties, influencing the melt flow less significantly than the same surface amount of broad size distribution coarse calcium carbonate filler particles. However, due to increased nucleation, the crystallization behavior on cooling showed a markedly more rapid onset in the case of fine sub-micrometer filler particle size. To control further and optimize the thermal response properties of a filling compound for improved properties in additive manufacturing processing through selective laser sintering, the possibility to combine precisely defined particle size distributions has been studied, thereby combining the benefits of each particle size range within the chosen material size distribution contributes to the matrix. The melt flow at 190 °C, the melting speed, melting and crystallization point as well as crystallization time at 170 °C were analyzed. The thermal and flow properties of a polyamide 12 matrix can potentially be optimized with a combination of a precise amount of coarse and fine calcium carbonate filler. The improvements were exemplified using a twin-screw extruder for compounding, indicating the potential for optimizing functionally filled polymer in additive manufacturing

Efficient 3D Mapping and Modelling of Indoor Scenes with the Microsoft HoloLens: A Survey

The Microsoft HoloLens is a head-worn mobile augmented reality device. It allows a real-time 3D mapping of its direct environment and a self-localisation within the acquired 3D data. Both aspects are essential for robustly augmenting the local environment around the user with virtual contents and for the robust interaction of the user with virtual objects. Although not primarily designed as an indoor mapping device, the Microsoft HoloLens has a high potential for an efficient and comfortable mapping of both room-scale and building-scale indoor environments. In this paper, we provide a survey on the capabilities of the Microsoft HoloLens (Version 1) for the efficient 3D mapping and modelling of indoor scenes. More specifically, we focus on its capabilities regarding the localisation (in terms of pose estimation) within indoor environments and the spatial mapping of indoor environments. While the Microsoft HoloLens can certainly not compete in providing highly accurate 3D data like laser scanners, we demonstrate that the acquired data provides sufficient accuracy for a subsequent standard rule-based reconstruction of a semantically enriched and topologically correct model of an indoor scene from the acquired data. Furthermore, we provide a discussion with respect to the robustness of standard handcrafted geometric features extracted from data acquired with the Microsoft HoloLens and typically used for a subsequent learning-based semantic segmentation

A Comparative Neural Radiance Field (NeRF) 3D Analysis of Camera Poses from HoloLens Trajectories and Structure from Motion

Neural Radiance Fields (NeRFs) are trained using a set of camera poses and associated images as input to estimate density and color values for each position. The position-dependent density learning is of particular interest for photogrammetry, enabling 3D reconstruction by querying and filtering the NeRF coordinate system based on the object density. While traditional methods like Structure from Motion are commonly used for camera pose calculation in pre-processing for NeRFs, the HoloLens offers an interesting interface for extracting the required input data directly. We present a workflow for high-resolution 3D reconstructions almost directly from HoloLens data using NeRFs. Thereby, different investigations are considered: Internal camera poses from the HoloLens trajectory via a server application, and external camera poses from Structure from Motion, both with an enhanced variant applied through pose refinement. Results show that the internal camera poses lead to NeRF convergence with a PSNR of 25\,dB with a simple rotation around the x-axis and enable a 3D reconstruction. Pose refinement enables comparable quality compared to external camera poses, resulting in improved training process with a PSNR of 27\,dB and a better 3D reconstruction. Overall, NeRF reconstructions outperform the conventional photogrammetric dense reconstruction using Multi-View Stereo in terms of completeness and level of detail.Comment: 7 pages, 5 figures. Will be published in the ISPRS The International Archives of Photogrammetry, Remote Sensing and Spatial Information Science

Solving the nuclear dismantling project scheduling problem by combining mixed-integer and constraint programming techniques and metaheuristics

Scheduling of megaprojects is very challenging because of typical characteristics, such as expected long project durations, many activities with multiple modes, scarce resources, and investment decisions. Furthermore, each megaproject has additional specific characteristics to be considered. Since the number of nuclear dismantling projects is expected to increase considerably worldwide in the coming decades, we use this type of megaproject as an application case in this paper. Therefore, we consider the specific characteristics of constrained renewable and non-renewable resources, multiple modes, precedence relations with and without no-wait condition, and a cost minimisation objective. To reliably plan at minimum costs considering all relevant characteristics, scheduling methods can be applied. But the extensive literature review conducted did not reveal a scheduling method considering the special characteristics of nuclear dismantling projects. Consequently, we introduce a novel scheduling problem referred to as the nuclear dismantling project scheduling problem. Furthermore, we developed and implemented an effective metaheuristic to obtain feasible schedules for projects with about 300 activities. We tested our approach with real-life data of three different nuclear dismantling projects in Germany. On average, it took less than a second to find an initial feasible solution for our samples. This solution could be further improved using metaheuristic procedures and exact optimisation techniques such as mixed-integer programming and constraint programming. The computational study shows that utilising exact optimisation techniques is beneficial compared to standard metaheuristics. The main result is the development of an initial solution finding procedure and an adaptive large neighbourhood search with iterative destroy and recreate operations that is competitive with state-of-the-art methods of related problems. The described problem and findings can be transferred to other megaprojects

Pose Normalization of Indoor Mapping Datasets Partially Compliant with the Manhattan World Assumption

In this paper, we present a novel pose normalization method for indoor mapping point clouds and triangle meshes that is robust against large fractions of the indoor mapping geometries deviating from an ideal Manhattan World structure. In the case of building structures that contain multiple Manhattan World systems, the dominant Manhattan World structure supported by the largest fraction of geometries is determined and used for alignment. In a first step, a vertical alignment orienting a chosen axis to be orthogonal to horizontal floor and ceiling surfaces is conducted. Subsequently, a rotation around the resulting vertical axis is determined that aligns the dataset horizontally with the coordinate axes. The proposed method is evaluated quantitatively against several publicly available indoor mapping datasets. Our implementation of the proposed procedure along with code for reproducing the evaluation will be made available to the public upon acceptance for publication

Influence of the Surface Modification of Calcium Carbonate on Polyamide 12 Composites

In previous investigations, it was found that the thermal properties of a polyamide 12 compound can be manipulated, using a designed filler, to improve the melting as well as crystallization behavior, determined for selective laser sintering. A common downside of the introduction of a non-flexing mineral filler is the reduction of the mechanical properties, such as ductility. This paper investigates the influence of content and surface modification of limestone on the mechanical properties. The aim is to understand the effect of an optimized coupling agent on the properties of a compound, containing polyamide 12 filled with 10 wt % of surface modified calcium carbonate. A range of four mineral filler modifications was chosen to investigate their coupling effect, namely 6-amino hexanoic acid, ε-caprolactam, l-arginine or glutamic acid. The in advance surface modified fillers were then each used in combination with the polyamide 12 in a twin-screw extrusion process. With an optimized surface modifying agent, the tensile strength as well as elongation at break can be improved in comparison with uncoated filler implementation, such that up to 60% of the loss of ductility and toughness of a final part when using an untreated filler could be regained using an optimized surface modifier at a correct amount. With the tested filler grade and the specific tested filler amount, the optimized amount of 6-amino hexanoic acid was approx. 2.5 mmol of treatment agent per 100 m2 of CaCO3. These found improvements in a twin-screw extruded polyamide 12 compound show the possible usage of modified calcium carbonate as a functional filler in additive manufacturing and can potentially be transferred in a subsequent investigation in the selective laser sintering process