Study of the applicability of cognitive path algorithms for 3D indoor navigation

C

Generation of navigation graphs for indoor space

This article proposes a comprehensive approach to computing a navigation graph for an indoor space. It focuses on a single floor, but the work is easily extensible to multi-level spaces. The approach proceeds by using a formal model, based on the combinatorial map but enhanced with geometric and semantic information. The process is almost fully automatic, taking as input the building plans providing the geometric structure of the floors and semantics of the building, such as functions of interior spaces, portals, etc. One of the novel aspects in this work was the use of combinatorial maps and their duals to provide a compact formal description of the topology and connectivity of the indoor structure represented by a connected, embedded graph. While making use of existing libraries for the more routine computational geometry involved, the research develops several new algorithms, including one for computing the local kernel of a region. The process is evaluated by means of a case study using part of a university building

Extending indoor open street mapping environments to navigable 3D citygml building models: Emergency response assessment

© Authors 2018. Disaster scenarios in high-rise buildings such as the Address Downtown, Dubai or Grenfell Tower, London have showed ones again the importance of data information availability for emergency management in buildings. 3D visualization of indoor routing services using extensive and high quality geographic data sources is essential for spatial analysis in emergency responses. In order to facilitate emergency response simulations, a combination of geometrical, graphical and semantic information is essential. Successful and efficient emergency evacuation responses is facilitated by the availability of both digital static and dynamic information of the incident site. However, interruptions may be encountered with the availability of dynamic data, where static data developed using indoor navigation ontologies serve as an alternative to inform the first responders. Thus, it is necessary to obtain a firm, interactive and quasi-realistic virtual simulation of the building environments. Voxelized CityGML models imported into voxel based hazard simulation systems fits well into the simulation algorithm requirements (Groger et al., 2008; Moreno et.al, 2010). Therefore, the research investigates an alternative platform for generating CityGML spatial analysis models. LoD4 models are developed using Computer Aided Design (Auto CAD) 2D files, crowdsourced geo-data (OpenStreetMap) and open source tools. A combination of software packages is utilized for 3D reconstruction of building interiors. This process is achieved through a Java application developed by researchers at Heidelberg University. Conclusions drawn from the research validate the 3D CityGML model generation process as an international standard to effectively enhance the outcome of emergency evacuation simulations of high rise buildings

An automated 3D modeling of topological indoor navigation network

© 2015, Springer Science+Business Media Dordrecht. Indoor navigation is important for various applications such as disaster management, building modeling, safety analysis etc. In the last decade, indoor environment has been a focus of wide research that includes development of indoor data acquisition techniques, 3D data modeling and indoor navigation. In this research, an automated method for 3D modeling of indoor navigation network has been presented. 3D indoor navigation modeling requires a valid 3D model that can be represented as a cell complex: a model without any gap or intersection such that two cells (e.g. room, corridor) perfectly touch each other. This research investigates an automated method for 3D modeling of indoor navigation network using a geometrical model of indoor building environment. In order to reduce time and cost of surveying process, Trimble LaserAce 1000 laser rangefinder was used to acquire indoor building data which led to the acquisition of an inaccurate geometry of building. The connection between surveying benchmarks was established using Delaunay triangulation. Dijkstra algorithm was used to find shortest path in between building floors. The modeling results were evaluated against an accurate geometry of indoor building environment which was acquired using highly-accurate Trimble M3 total station. This research intends to investigate and propose a novel method of topological navigation network modeling with a less accurate geometrical model to overcome the need of required an accurate geometrical model. To control the uncertainty of the calibration and of the reconstruction of the building from the measurements, interval analysis and homotopy continuation will be investigated in the near future

Automated construction of variable density navigable networks in a 3D indoor environment for emergency response

Widespread human-induced or natural threats on buildings and their users have made preparedness and quick response as crucial issues for saving human lives. Available information about an emergency scene, e.g. the building structure, material and trapped people helps for decision-making and organizing rescue operations. The ability to evaluate potential scenarios for human evacuation, and then identifying the paths of egress during an emergency is critical for rescue and emergency services. Good quality models supporting real, or near-real, time decision-making and allowing the implementation of automated methods are highly desirable. In this paper, we propose a new automated method for deriving a navigable network in a 3D indoor environment, including a full 3D topological model which may be used not only for standard navigation but also for finding alternative egress routes and simulating phenomena associated with disasters such as fire spread and heat transfer

3D indoor topological modelling based on homotopy continuation

Indoor navigation is important for various applications such as disaster management, building modelling and safety analysis. In the last decade, the indoor environment has been a focus of extensive research that includes the development of indoor data acquisition techniques, three-dimensional (3D) data modelling and indoor navigation. 3D indoor navigation modelling requires a valid 3D geometrical model that can be represented as a cell complex: a model without any gap or intersection such that the two cells, a room and corridor, should perfectly touch each other. This research is to develop a method for 3D topological modelling of an indoor navigation network using a geometrical model of an indoor building environment. To reduce the time and cost of the surveying process, a low-cost non-contact range-based surveying technique was used to acquire indoor building data. This technique is rapid as it requires a shorter time than others, but the results show inconsistencies in the horizontal angles for short distances in indoor environments. The rangefinder was calibrated using the least squares adjustment and a polynomial kernel. A method of combined interval analysis and homotopy continuation was developed to model the uncertainty level and minimize error of the non-contact range-based surveying techniques used in an indoor building environment. Finally, a method of 3D indoor topological building modelling was developed as a base for building models which include 3D geometry, topology and semantic information. The developed methods in this research can locate a low-cost, efficient and affordable procedure for developing a disaster management system in the near-future

Three dimensional compact abstract cell complexes topological data structure for buildings in CityGML

As the significance of visualising objects in three dimensional is now recognised, most city modelling approaches support 3D primitives in the construction (3D) of objects and visualisation. Although the visualisation of city models is in 3D, the topological information maintained remains in two dimensional (2D). This hinders the 3D model to serve its full potential, as the topological information that gives meaning to the objects is not preserved explicitly. The support of 3D topology is crucial for 3D spatial analysis that requires connectivity information and adjacencies in order to produce accurate output in 3D. This research investigates the implementation of a 3D topological model specifically using the Compact Abstract Cell Complexes (CACC) topological data structure for preserving the topological information of buildings in City Geographic Markup Language (CityGML). As the international standard for city modelling, the topological component of CityGML is in 2D via the simple topology-incidence. The use of the simple topology-incidence mechanism within CityGML allows only explicitly stored surfaces can be referenced. This then brings up the issue of inconsistent visualisation which is usually resolved by modelling the two buildings with two separate surfaces representing the common surface. However, the connectivity information between the two connected buildings are not preserved in CityGML as they do not share the same explicitly stored surface. Three objectives were established for the study namely to determine the specifications of a topological data structure for preserving topological information of buildings in CityGML, to implement a topological structure for buildings in CityGML that supports connectivity queries and adjacency analyses for city modelling, and to validate the proposed topological data structure in terms of geometric and topological properties in comparison to the existing CityGML topology mechanism. Several tasks were carried out to complete this research, including extraction of geometrical properties from CityGML, generation of topological links, adjacency analysis using topological information, and visualisation of 3D model and adjacency analysis results. The absence of a comprehensive topological model within CityGML made it necessary to use the geometric properties of the buildings in CityGML as a stand-in model to extract the topological properties that would subsequently be the basis for generating topological links. The CACC topological model preserves topological information by building topological links where points are connected to build alpha-0 links (1D lines), alpha-0 links are connected to build alpha-1 links (2D surfaces), alpha-1 links are connected to build alpha-2 links (3D volumes) and alpha-3 links represent the connectivity between 3D buildings. This allows connectivity between elements of different dimension as any link can be decomposed to its related lower dimension elements. Next, by implementing CACC topological model, the connectivity information for two buildings that are connected but modelled with two separate surfaces can be preserved. The support of topological information via the CACC topological model also allows the seamless execution of adjacency queries between building elements, including elements of different dimensions

AN IFC-BASED FRAMEWORK FOR OPTIMIZING LEVEL OF PREFABRICATION IN INDUSTRIALIZED BUILDING SYSTEMS

Ph.DDOCTOR OF PHILOSOPH