Crowd sourced mapping with robust structural features
A location and mapping service is described that creates a global database of indoor navigation maps through crowd-sourcing and data fusion technologies. The navigation maps consist of a database of geo-referenced, uniquely described features in the multi-dimensional sensor space (e.g., including structural, RF, magnetic, image, acoustic, or other data) that are collected automatically as a tracked mobile device is moved through a building (e.g. a person with a mobile phone or a robot). The feature information can be used to create building models as one or more tracked devices traverse a building.
1. A computer-implemented method for localizing a mobile device at a structure and generating or updating maps representing the structure, the method comprising:
detect a structural feature associated with the structure using sensor data associated with the mobile device while traversing the detected structural feature;
upon detecting the structural feature, obtain signal data associated with the detected structural feature's environment;
generate a mobile structure map representing the structure at the mobile device using the sensor data;
communicate a feature descriptor to a server communicatively coupled to a dataset comprised of previously received feature descriptors and one or more mobile structure maps generated using the previously received feature descriptors, each feature descriptor associated with a corresponding structural feature and including sensor data used by other mobile devices to detect the corresponding structural feature, signal data obtained by the other mobile devices upon detecting the corresponding structural feature, or a combination thereof; and
in response to the communicated feature descriptor, receive a map correction from the server that corrects the detected structural feature's location on the mobile structure map.
2. The computer-implemented method of claim 1 , wherein the sensor data describes physical information about the detected structural feature and includes inertial sensor data, pressure sensor data, location data, or a combination thereof.
3. The computer-implemented method of claim 1 , wherein the obtained signal data provides differentiating information to further distinguish the corresponding structural feature and includes radio frequency signal data, magnetic field data, vibration data, acoustic signature data, image data, light data, or a combination thereof.
4. The computer-implemented method of claim 1 , wherein the detected structural features serves as a trigger for the mobile device to scan for signal data associated with the detected structural feature's environment.
5. The computer-implemented method of claim 1 , wherein the mobile device continually scans for signal data associated with the detected structural feature's environment, wherein the method further comprises:
generate a timestamp upon detecting structural features that serves as a reference point for the mobile device to aggregate obtained signal data in predefined time windows around the reference point.
6. The computer-implemented method of claim 1 , wherein the method further comprises:
upon receiving the map correction, refine one or more path parameters describing a path followed by the mobile device, the one or more path parameters including heading, scale, drift, mobile device location, or a combination thereof.
7. A computing system for localizing a mobile device traversing a structure and generate or update maps representing the structure, the computing system comprising:
one or more processors; and
a memory communicatively coupled to the processor, the memory bearing instructions that, when executed on the one or more processors, cause the computing system to at least:
receive a feature descriptor comprised of sensor data used by the mobile device to detect a structural feature while traversing the detected structural feature;
determine whether a match exists between the detected structural feature and existing structural features described by previously received feature descriptors aggregated in a dataset using match scores, each match score comprised of similarity scores generated for one or more match score factors based on data from the feature descriptor and data associated with a particular existing structural feature compiled from the previously received feature descriptors;
upon determining the match exists, communicate a map correction that corrects the detected structural feature's location on a mobile structure map generated by the mobile device using the sensor data.
8. The computing system of claim 7 , wherein the one or more match score factors include a location-based factor that matches the detected structural feature and the particular existing structural feature based on similarities in corresponding locations and error bound information, the location-based factor's similarity score computed using: horizontal error bound overlap; elevation error bound overlap; feature density within the horizontal error bound; feature density within the elevation error bound; or a combination thereof.
9. The computing system of claim 7 , wherein the one or more match score factors include a structure-based factor that matches the detected structural feature and the particular existing structural feature based on similarities in structural characteristics, the structure-based factor's similarity score computed based upon matches between one or more corresponding structural characteristics of the detected structural feature and the particular existing structural feature.
10. The computing system of claim 7 , wherein the one or more match score factors include a signal-based factor that matches the detected structural feature and the particular existing structural feature based on similarities in signal data associated with corresponding environments, the signal-based factor's similarity score computed based upon one or more matches in signal data associated with the environment corresponding to the detected structural feature and the particular existing structural feature.
11. The computing system of claim 7 , wherein the sensor data describes physical information about the detected structural feature and includes inertial sensor data, pressure sensor data, location data, or a combination thereof.
12. The computing system of claim 7 , wherein feature descriptors further include signal data associated with a corresponding structural feature's environment that provides differentiating information to further distinguish the corresponding structural feature, the signal data including radio frequency signal data, magnetic field data, vibration data, acoustic signature data, image data, light data, or a combination thereof.
13. The computing system of claim 7 , wherein the feature descriptor message is a parent message describing the detected structural feature as a whole.
14. The computing system of claim 7 , wherein the feature descriptor message is a child message describing a sub-portion of the detected structural feature.
15. The computing system of claim 7 , wherein the instructions further cause the computing system to filter feature descriptors using one or more quality control filters prior to determining matches to exclude feature descriptors that fail to satisfy one or more quality standards from being included in the dataset.
16. The computing system of claim 7 , wherein the instructions further cause the computing system to merge the detected structural feature with the particular existing feature by merging data in the feature descriptor with data from previously received feature descriptors describing the particularly existing structural feature.
17. The computing system of claim 7 , wherein the instructions further cause the computing system to add the detected structural feature to a structural map generated using the previously received feature descriptors aggregated in the dataset.
18. A non-transitory computer-readable storage medium comprising instructions tangibly embodied thereon that, when executed by a computing device adapted to localize a mobile device traversing a structure and generate or update maps representing the structure, cause the computing device to at least:
receive a feature descriptor comprised of sensor data used by the mobile device to detect a structural feature while traversing the detected structural feature and signal data associated with the detected structural feature's environment that provides differentiating information to further distinguish the detected structural feature from other structural features;
identify the structure associated with the detected structural feature using the received feature descriptor;
determine whether a match exists between the detected structural feature and a structural feature existing in a structure map generated using previously received feature descriptors aggregated in a dataset, the match determined based on a match scores comprised of similarity scores generated for one or more match score factors based on data from the feature descriptor and data associated with the existing structural feature compiled from the previously received feature descriptors; and
upon determining the match exists, communicate a map correction that corrects the detected structural feature's location on a mobile structure map generated by the mobile device using the sensor data.
19. The non-transitory computer-readable storage medium of claim 18 , wherein the signal data includes radio frequency (“RF”) signal data; magnetic field data; vibration data; acoustic signature data; image data; light data; or a combination thereof, the RF signal data including signal strength; signal statistics; signal identifiers; signal source identifiers; signal source direction; or a combination thereof.
20. The non-transitory computer-readable storage medium of claim 18 , wherein the instructions further cause the computing device to identify the detected structural feature, the structure associated with the detected structural feature, or a combination thereof using the signal data.