3D Property Mapping With Marker-Based Labeling for Glass Surfaces
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Solution Overview
Problem
Conventional property monitoring systems using drones struggle to detect and map surfaces that are not easily detectable, such as glass walls, glass windows, closed doors, and moving objects, due to limitations in sensor capabilities.
Innovation Solution
A robotic device equipped with cameras and processors generates a three-dimensional map of a property by using markers installed on these surfaces, which provide encoded data to update the map and include features undetectable by standard mapping sensors, allowing for accurate labeling and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional mapping sensors are used on a drone, then the drone can navigate and map most property features, but surfaces such as glass walls, glass windows, closed doors, and moving objects cannot be detected
Solution Approach 1:
The patent introduces markers as intermediary objects that are placed on surfaces difficult to detect (glass walls, windows, doors). These markers serve as mediators between the mapping system and the previously undetectable surfaces, allowing the drone to detect and map these surfaces through the markers rather than directly through the challenging surfaces themselves.
Solution Approach 2:
The markers used in the patent utilize distinct visual characteristics (colors, patterns, reflectivity) that make them easily distinguishable from the surrounding environment and from each other. This visual differentiation allows the mapping sensors to reliably detect and identify markers on various surfaces including glass and moving objects, overcoming the detectability limitations of conventional sensors.
2Reliability
If markers are installed on surfaces to enable detection, then previously undetectable surfaces can be mapped, but the system complexity increases due to marker installation and recognition requirements
Solution Approach 1:
The markers are designed to be self-identifying through their encoded visual patterns. When detected by the drone's sensors, the markers automatically provide their identification information without requiring additional processing equipment or complex recognition algorithms. The marker itself carries the necessary information (through its visual encoding) to identify the surface it is attached to, making the system self-sufficient.
Solution Approach 2:
The patent encodes surface identification information in the visual appearance of markers (color, pattern, reflectivity properties) rather than requiring complex mechanical or electronic identification systems. This transforms the identification problem from a mechanical/electronic dimension to an optical dimension, allowing simple sensors to extract rich information about the marked surfaces.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a storage device, for generating a three-dimensional map of a property. The method includes storing at least a portion of an initial map modification data structure, receiving an instruction that instructs the robotic device to initiate property mapping, obtaining image data describing a portion of the property that is mounted to the robotic device, analyzing the obtained image data to determine whether the image data depicts a marker, in response to a determination that the obtained image data depicts a marker, determining the pose of the camera that is mounted to the robotic device, updating the initial map modification data structure using the pose of the camera that is mounted to the robotic device, obtaining an initial three-dimensional map of the property; and modifying the initial three-dimensional map of the property based on the updated map modification data structure.