Indoor Navigation Path Modeling From Architectural Floor Plans
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Solution Overview
Problem
Current indoor navigation systems face challenges in accurately mapping and generating walking paths within buildings due to the lack of geospatial data and reliance on GPS signals, which are unreliable indoors, leading to inefficient and resource-intensive manual processes.
Innovation Solution
A navigation platform that utilizes modeling techniques, such as vectorization, convex hull processing, and pathfinding models, to automatically generate paths based on architectural floor plans, reducing the need for manual mapping and conserving resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual mapping of walking paths is used, then path generation can be performed, but it is time-consuming and resource-intensive
Solution Approach 1:
The system performs preliminary action by automatically generating walking paths during off-peak hours or in advance, using computational models to pre-calculate optimal routes before users need them. This eliminates the need for real-time path calculation during user navigation, thereby improving productivity while reducing the time users experience waiting for path generation.
Solution Approach 2:
The system creates simplified copies of the building's geometric structure through vectorized representations and convex hull approximations. Instead of working with detailed architectural drawings, the system uses simplified polygonal models that capture essential spatial relationships, enabling rapid automated path generation without manual mapping while maintaining navigation accuracy.
2Productivity
If automated path generation is implemented, then time and resources are conserved, but accuracy of indoor navigation is challenged due to lack of geospatial data
Solution Approach 1:
The system introduces an intermediary layer of geometric modeling that translates architectural floor plans into navigation-ready representations. Vectorization models convert building layouts into precise polygonal vectors, and convex hull algorithms create simplified geometric approximations that preserve spatial relationships. These intermediary models enable automated path generation while maintaining the precision needed for accurate indoor navigation, bridging the gap between automated processing and navigation accuracy.
3Reliability
If GPS localization is used for indoor navigation, then location can be provided, but it lacks reliability due to signal blockage
Solution Approach 1:
The system extracts the positioning function from GPS satellite signals and implements it through alternative means suitable for indoor environments. By removing dependence on external satellite signals that are blocked by buildings, the system uses Wi-Fi positioning, Bluetooth beacons, or other indoor-appropriate localization technologies that operate reliably within indoor spaces, thereby maintaining location accuracy without GPS signal blockage.
Data Source
AI summary
A device may receive an architectural floor plan of an interior of a building, and may process the architectural floor plan, with a vectorization model, to generate a vectorized floor plan of polygons. The device may process the vectorized floor plan, with a convex hull model, to create convex hull polygons around the polygons of the vectorized floor plan, and may reduce a quantity of vertices associated with the convex hull polygons to generate simplified convex hull polygons. The device may generate, based on the simplified convex hull polygons, one of a visibility graph that identifies potential paths through the interior of the building, or a walking path network through the interior. The device may process the one of the visibility graph or the walking path network, with a pathfinding model, to identify paths through the interior of the building, and may perform actions based on the identified paths.