Collaborative creation of indoor maps
First Claim
1. A computer-implemented method for generating a building map, the method comprising:
- receiving sensor data from each tracked device among a plurality of tracked devices, the sensor data comprising location data and inertial sensor data;
generating motion data based on the sensor data, the motion data indicative of a path taken by a user associated with the tracked device;
inferring at least one motion from the motion data;
inferring one or more building features, including a location and a location error bound of each inferred building feature, wherein the inferred building features are based on;
the location data, the at least one motion, and associated descriptive information;
generating a graphical feature map indicative of user movement by spatially and temporally linking inferred building features based on a time of discovery, the inferred location, and the location error bound of each inferred building feature;
merging the graphical feature maps from each tracked device to generate a building map comprising building features merged from one or more inferred building features; and
determining a location of each building feature based on a weighted average of the inferred locations and the location error bounds of the one or more associated inferred building features.
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Abstract
This disclosure provides techniques for the creation of maps of indoor spaces. In these techniques, an individual or a team with no mapping or cartography expertise can contribute to the creation of maps of buildings, campuses or cities. An indoor location system can track the location of contributors in the building. As they walk through indoor spaces, an application may automatically create a map based on data from motion sensors by both tracking the location of the contributors and also inferring building features such as hallways, stairways, and elevators based on the tracked contributors'"'"' motions as they move through a structure. With these techniques, the process of mapping buildings can be crowd sourced to a large number of contributors, making the indoor mapping process efficient and easy to scale up.
207 Citations
23 Claims
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1. A computer-implemented method for generating a building map, the method comprising:
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receiving sensor data from each tracked device among a plurality of tracked devices, the sensor data comprising location data and inertial sensor data; generating motion data based on the sensor data, the motion data indicative of a path taken by a user associated with the tracked device; inferring at least one motion from the motion data; inferring one or more building features, including a location and a location error bound of each inferred building feature, wherein the inferred building features are based on;
the location data, the at least one motion, and associated descriptive information;generating a graphical feature map indicative of user movement by spatially and temporally linking inferred building features based on a time of discovery, the inferred location, and the location error bound of each inferred building feature; merging the graphical feature maps from each tracked device to generate a building map comprising building features merged from one or more inferred building features; and determining a location of each building feature based on a weighted average of the inferred locations and the location error bounds of the one or more associated inferred building features. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A computing system for generating a building map, the computing system comprising:
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a processor; a memory communicatively coupled to the processor, the memory bearing instructions that, when executed on the processor, cause the computing system to at least; receive sensor data from each tracked device among a plurality of tracked devices, the sensor data comprising location data and inertial sensor data; generate motion data based on the sensor data, the motion data indicative of a path taken by a user associated with the tracked device; infer at least one motion from the motion data; infer one or more building features, including a location and a location error bound of each building feature, wherein the inferred building features are based on;
the location data, the at least one motion, and associated descriptive information;generate a graphical feature map indicative of user movement by spatially and temporally linking inferred building features based on a time of discovery, the inferred location and location error bound of each inferred building feature; merge the graphical feature maps from each tracked device to generate a building map comprising building features merged from one or more inferred building features; and determine a location of each building feature based on a weighted average of the inferred locations and the location error bounds of the one or more associated inferred building features. - View Dependent Claims (13, 14, 15, 16, 17)
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18. A computer readable storage medium comprising instructions that, when executed on a computing system configured generate a building map, cause the computing system to at least:
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receive sensor data from each tracked device among a plurality of tracked devices, the sensor data comprising location data and inertial sensor data; generate motion data based on the sensor data, the motion data indicative of a path taken by a user associated with the tracked device; infer at least one motion from the motion data; infer one or more building features, including a location and a location error bound of each inferred building feature, wherein the inferred building features are based on;
the location data, the at least one motion, and associated descriptive information;generate a graphical feature map indicative of user movement by spatially and temporally linking inferred building features based on a time of discovery, the inferred location and location error bound of each inferred building feature; merge the graphical feature maps from each tracked device to generate a building map comprising building features merged from one or more inferred building features; and determine a location of each building feature based on a weighted average of the inferred locations and the location error bounds of the one or more associated inferred building features. - View Dependent Claims (19, 20, 21, 22, 23)
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Specification