Abstract
Navigation systems help agents find the right (optimal) path from the origin to the desired destination. Current navigation systems mainly offer the shortest (distance or time) path as the default optimal path. However, under certain circumstances, having a least-top-exposed path can be more interesting. For instance, on a rainy day, a path with as many places as possible covered by roofs/shelters is more attractive and pragmatic, since roofs/shelters can offer protection from rain. In this paper, we name environments that covered by roofs/shelters but not completely enclosed like indoors as “top-bounded environments/spaces” (e.g., porches), which are generally formed by built structures. This kind of space is completely missing in current navigation models and systems. Thus, we investigate how to use it for space-based navigation. After proposing a definition, a space model, and attributes of top-bounded spaces, we introduce a projection-based approach to generate them. Then, taking a pedestrian as an example agent, we select generated spaces considering whether the agent can visit/use the identified spaces. Finally, examples and a use case study demonstrate that our research can help to include top-bounded spaces in navigation systems/models. More navigation path types (e.g., least-top-exposed) can be offered for different agents (such as pedestrians, drones or robots).
Highlights
Navigation is described as the method of determining the direction of a familiar goal across unfamiliar terrain [1] or the process of orientation to reach a specific distant destination from the origin [2]
We concentrate on the definition, creation, trimming, and selection of top-bounded spaces for a navigation system
The demonstrations and experiments indicate that the creation of top-bounded spaces is feasible given existing 3D standards such as CityGML or IFC
Summary
Navigation is described as the method of determining the direction of a familiar goal across unfamiliar terrain [1] or the process of orientation to reach a specific distant destination from the origin [2]. Three types of spaces (environments) can be defined in navigation: completely bounded space (indoor), unbounded space (outdoor), and semi-bounded [12]. Top-bounded spaces can be a good alternative choice when offering a least-top-exposed path for agents, because indoor and top-bounded spaces are two environments that have roofs/shelters. The former is often regarded as non-public (i.e., for specific agents only), while the latter is mostly public [15]. Top-bounded spaces are completely missing in current navigation models and systems This omission can be partly explained by the fact that modelling a semi-bounded space is a very challenging task [12] because space is a three-dimensional boundless and extensible component.
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