System and method for localizing a trackee at a location and mapping the location using signal-based features

• US 9,664,521 B2
• Filed: 04/25/2014
• Issued: 05/30/2017
• Est. Priority Date: 06/12/2012
• Status: Active Grant

• Current Assignee: TRX Systems, Inc.
• Original Assignee: TRX Systems, Inc.
• Inventors: Napora, Jared, Kordari, Kamiar, Verma, Ruchika, Funk, Benjamin E., Teolis, Carole, Bandyopadhyay, Amrit
• Primary Examiner(s): PAIGE, TYLER D
• Application Number:
  US14/262,627
• Publication Number:
  US 20150285638A1
• Time in Patent Office: 1,131 Days
• Field of Search: 701409-540, 345419
• CPC Class Codes: G01C 21/1652 with ranging devices, e.g. LIDAR or RADAR
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G01C 21/1656 with passive imaging devices, e.g. cameras
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: G01C 21/3844 Data obtained from position sensors only, e.g. from inertial navigation
• CPC Class Codes: G01C 21/3848 Data obtained from both position sensors and additional sensors
• CPC Class Codes: G01S 19/13 Receivers
• CPC Class Codes: G01S 19/39 the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
• CPC Class Codes: G01S 5/012 Identifying whether indoors or outdoors
• CPC Class Codes: G01S 5/014 Identifying transitions between environments
• CPC Class Codes: G01S 5/015 between indoor and outdoor environments

Abstract

A system and method for recognizing features for location correction in Simultaneous Localization And Mapping operations, thus facilitating longer duration navigation, is provided. The system may detect features from magnetic, inertial, GPS, light sensors, and/or other sensors that can be associated with a location and recognized when revisited. Feature detection may be implemented on a generally portable tracking system, which may facilitate the use of higher sample rate data for more precise localization of features, improved tracking when network communications are unavailable, and improved ability of the tracking system to act as a smart standalone positioning system to provide rich input to higher level navigation algorithms/systems. The system may detect a transition from structured (such as indoors, in caves, etc.) to unstructured (such as outdoor) environments and from pedestrian motion to travel in a vehicle. The system may include an integrated self-tracking unit that can localize and self-correct such localizations.

Claims

1. A computer-implemented method of localizing a trackee at a location and generating or updating a map of the location based on sensor information, the method being implemented on a computer system that includes one or more physical processors programmed by one or more modules, the method comprising:

identifying, by a feature detection module, at least one sensor feature based on a combination of;

inertial sensor data, magnetic data, radiation data, and signal strength data, wherein the at least one sensor feature includes a plurality of measurements that measure a motion of the trackee at the location and being identified based on a first subset of the plurality of measurements;

utilizing the at least one sensor feature, that includes a plurality of measurements that measure a motion of the trackee at the location, to identify a landmark at the location;

determining, by a localization and mapping module, a location estimate that estimates the location of the trackee based on at least a second subset of the plurality of measurements that is the same as or different from the first subset of the plurality of measurements, wherein a landmark position of the landmark is determined based on the location estimate;

generating a feature message that includes information unique to the landmark and the landmark position on a path of the trackee;

generating or updating the map based on the feature message.

2. The computer-implemented method of claim 1, wherein the at least one sensor feature includes vector representations of one or more of magnetic data, radiation data, inertial data, and signal strength data.

3. The computer-implemented method of claim 1, wherein the landmark is identified by a feature descriptor detailing unique aspects of the landmark based on high sample rate data.

4. The computer-implemented method of claim 1, wherein the magnetic data includes an extrema or a sharp transition in magnetic magnitude.

5. The computer-implemented method of claim 1, wherein the magnetic data includes a minimum magnitude and a maximum magnitude.

6. The computer-implemented method of claim 1, wherein the landmark is not identified until the at least one sensor feature has been identified at the landmark position multiple times.

7. The computer-implemented method of claim 1, wherein the identification of the at least one sensor feature is further based on second sensor information.

8. The computer-implemented method of claim 7, wherein the second sensor information includes one or more of magnetic data, radiation data, inertial data, signal strength data, global positioning data, and light data.

9. The computer-implemented method of claim 1, wherein identifying the landmark includes correlating the at least one sensor feature to a structural feature.

10. The computer-implemented method of claim 1, wherein the information unique to the landmark includes a description comprising parameters of structural features of the landmark.

11. The computer-implemented method of claim 1, wherein generating or updating the map includes generating or updating the map based on the landmark position.

12. The computer-implemented method of claim 1, wherein the at least one sensor feature is detected from a tracking device carried, worn, or otherwise associated with the trackee.

13. A computer-implemented method being implemented on a computer system that includes one or more physical processors programmed by one or more modules, the method comprising:

identifying, by a first module, a sensor feature based on a combination of;

inertial sensor data, magnetic data, radiation data, and signal strength data, wherein the sensor feature includes a plurality of measurements representing a motion of a trackee at a location and being identified based on a first subset of the plurality of measurements;

correlating the sensor feature , that includes a plurality of measurements that measure a motion of the trackee at the location, to identify a landmark;

determining, by a second module, a location estimate that estimates the location of the trackee based on at least a second subset of the plurality of measurements that is the same as or different from the first subset of the plurality of measurements, wherein a landmark position of the landmark is determined based on the location estimate;

generating, by a third module, a feature message that includes information unique to the landmark and the landmark position on a path of the trackee;

generating or updating, by a fourth module, the map based on the feature message.

14. The computer-implemented method of claim 13, wherein the sensor feature includes vector representations of one or more of magnetic data, radiation data, inertial data, and signal strength data.

15. The computer-implemented method of claim 13, wherein the landmark is identified by a feature descriptor detailing unique aspects of the landmark based on high sample rate data.

16. The computer-implemented method of claim 13, wherein the magnetic data includes an extrema or a sharp transition in magnetic magnitude.

17. The computer-implemented method of claim 13, wherein the magnetic data includes a minimum magnitude and a maximum magnitude.

18. The computer-implemented method of claim 13, wherein the identification of the sensor feature is further based on second sensor information.

19. The computer-implemented method of claim 18, wherein the second sensor information includes one or more of magnetic data, radiation data, inertial data, signal strength data, global positioning data, and light data.

20. The computer-implemented method of claim 13, wherein the information unique to the landmark includes a description comprising parameters of structural features of the landmark.

21. The computer-implemented method of claim 13, wherein generating or updating the map includes generating or updating the map based on the landmark position.

22. The computer-implemented method of claim 13, wherein the sensor feature is detected from a tracking device carried, worn, or otherwise associated with the trackee.