US 9,733,091 B2Granted

Collaborative creation of indoor maps

AssigneeTrx Systems, Inc.

InventorsKamiar Kordari, Benjamin Funk, Carole Teolis, Jared Napora, John Karvounis, Dan Hakim, Christopher Giles, Carol Politi

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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.

Claims35

Dependent claims

A computer-implemented method for generating a building map of an indoor space, the method comprising:

collecting sensor data, including inertial sensor data, via an electronic network from each computing device among a plurality of computing devices;
using the sensor data to generate location data corresponding to an estimate of a location of each computing device;
using the sensor data to generate motion data corresponding to motions of each computing device;
using the location data and the motion data associated with each device to generate a three dimensional feature graph of building features associated with the indoor space comprising:
assigning one or more motions to be associated with a building feature;
and
inferring building features by using the motion data from each computing device by identifying the one or more motions associated with each building feature;
creating a graphical map from each three dimensional feature graph, representing a temporal sequence of events, comprising:
generating a node for each inferred building feature:
estimating a location of each node using the location data;
establishing location error bounds for each node;
and
generating links between nodes to represent spatial connections using the location of each node and a time of discovery for each inferred building feature;
correcting one or more of the estimates of node location and error bounds to compensate for drift of the estimate of location for one or more of the computing devices to create a plurality of corrected graphical maps;
and
merging a plurality of the nodes of the corrected graphical maps to generate the building map, the merging being based at least on a node type and a node location.

13 more elements

A computing system for generating a map of an indoor space, the computing system comprising:

a processor;
and
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, including inertial sensor data, at the processor via an electronic network from each computing device among a plurality of computing devices;
use the sensor data to generate location data indicative of a location of each computing device in the indoor space;
use the sensor data to generate motion data indicative of motions of each computing device in the indoor space, wherein the motion data corresponds to a path of each computing device;
generate a three dimensional feature graph of building features of the indoor space based on the motion data, the path and the location data of each computing device comprising:
assigning one or motions to be associated with a building feature;
and
identifying the one or more motions associated with each building feature;
create a graphical map from each three dimensional feature graph, representing a temporal sequence of events, comprising:
generating a node for each inferred building feature:
estimating a location of each node using the location data;
establishing location error bounds for each node;
and
generating links between nodes to represent spatial connections using the location of each node and a time of discovery for each inferred building feature;
and
merge a plurality of the nodes of the graphical maps to generate the map, the merging being based at least on a node type and a node location.

15 more elements

A computer-implemented method for generating a map of an indoor space, the method comprising:

receiving sensor data, including inertial sensor data, at the processor via an electronic network from each computing device among a plurality of computing devices;
using the sensor data to generate location data indicative of a location of each computing device in the indoor space;
using the sensor data to generate motion data indicative of motions of each computing device in the indoor space, wherein the motion data corresponds to a path of each computing device;
generating a three dimensional feature graph of building features of the indoor space based on the motion data, the path and the location data of each computing device comprising:
assigning one or motions to be associated with a building feature;
and
identifying the one or more motions associated with each building feature;
create a graphical map from each three dimensional feature graph, representing a temporal sequence of events, comprising:
generating a node for each inferred building feature:
estimating a location of each node using the location data;
establishing location error bounds for each node;
and
generating links between nodes to represent spatial connections using the location of each node and a time of discovery for each inferred building feature;
and
merging a plurality of the nodes of the graphical maps to generate the map, the merging being based at least on a node type and a node location.

12 more elements

Dependencies are inferred from the claim text.

Facts

Application: 14/178,605Filed 12 Feb 2014 · us provisional application
Priority: 14 Mar 2013
Published: US 2014/0278060 A118 Sep 2014
Granted: 15 Aug 2017
Term ends: Not estimatedThe source records don’t support an estimate.

Classification3 codes

G01C 21/206
Instruments for performing navigational calculations: specially adapted for indoor navigation
G01C 21/383
Characterised by the type of data: indoor data
G01C
Measuring distances, levels or bearings