SYSTEM AND METHOD FOR LOCALIZING A TRACKEE AT A LOCATION AND MAPPING THE LOCATION USING TRANSITIONS

• US 20150285636A1
• Filed: 04/25/2014
• Published: 10/08/2015
• Est. Priority Date: 06/12/2012
• Status: Active Grant

• Current Assignee: TRX Systems, Inc.
• Original Assignee: TRX Systems, Inc.
• Inventors: Funk, Benjamin E., Napora, Jared, Kordari, Kamiar, Verma, Ruchika, Bandyopadhyay, Amrit, Teolis, Carole
• Granted Patent: US 9,146,113 B1
• Time in Patent Office: Days
• US Class Current: 1/1
• 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 tracking a trackee between a first location and a second location, the method being implemented on a computer system that includes one or more physical processors programmed by one or more modules, the method comprising:

receiving, at a location transition detection module, signal information from a plurality of sensors;

identifying, by the location transition detection module, one or more available sensors among the plurality of sensors;

determining, by the location transition detection module, a status confidence value based on the signal information from the one or more available sensors; and

identifying, by the location transition detection module, a transition between the first location and the second location based on the confidence value and the signal information from the one or more available sensors.

2. The method of claim 1, wherein the first location is indoors and the second location is outdoors, the method further comprising changing a tracking algorithm employed to track the trackee from a first tracking algorithm to a second tracking algorithm based on the transition from the first location to the second location.

3. The method of claim 1, wherein the first location is outdoors and the second location is indoors, the method further comprising changing a tracking algorithm employed to track the trackee from a first tracking algorithm to a second tracking algorithm based on the transition from the first location to the second location.

4. The method of claim 1, wherein the first location is inside of a moving vehicle and the second location is outside of a moving vehicle, the method further comprising changing a tracking algorithm employed to track the trackee from a first tracking algorithm to a second tracking algorithm based on the transition from the first location to the second location.

5. The method of claim 1, wherein the first location is outside of a moving vehicle and the second location is inside of a moving vehicle, the method further comprising changing a tracking algorithm employed to track the trackee from a first tracking algorithm to a second tracking algorithm based on the transition from the first location to the second location.

6. The method of claim 1, wherein the signal information includes one or more of GPS signal quality, magnetic signature, electrical signature, and light.

7. The method of claim 1, further comprising:

identifying, by the feature detection module, the transition as a landmark;

determining, by a localization and mapping module, a location estimate that estimates a location of the trackee based on the landmark; and

generating or updating, by the localization and mapping module, a map including the location.

8. The method of claim 1, wherein the first location is a structured environment and the second location is an unstructured environment, the method further comprising changing a tracking algorithm employed to track the trackee from a first tracking algorithm to a second tracking algorithm based on the transition from the first location to the second location.

9. The method of claim 1, wherein the first location is an unstructured environment and the second location is a structured environment, the method further comprising changing a tracking algorithm employed to track the trackee from a first tracking algorithm to a second tracking algorithm based on the transition from the first location to the second location.

10. The method of claim 1, wherein the confidence value is based on one or more confidence values and indicates whether the trackee is indoors, outdoors or in an unknown location.

11. The method of claim 10, wherein each of the one or more confidence values is based on a type of the one or more available sensors.

12. The method of claim 1, wherein the confidence value indicates whether the trackee is traveling by foot or by vehicle, the method further comprising changing a tracking algorithm employed to track the trackee from a first tracking algorithm to a second tracking algorithm based on the transition from the first location to the second location.

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:

receiving signal information, by a first module, from one or more available sensors of a plurality of sensors;

determining, by the first module, a confidence value based on the signal information from the one or more available sensors; and

identifying, by the first module, a transition between a first location and a second location based on the confidence value and the signal information from the one or more available sensors.

14. The method of claim 13, wherein the first location is indoors and the second location is outdoors.

15. The method of claim 13, wherein the first location is outdoors and the second location is indoors.

16. The method of claim 13, wherein the first location is inside of a moving vehicle and the second location is outside of a moving vehicle, the method further comprising changing a tracking algorithm employed to track the trackee from a first tracking algorithm to a second tracking algorithm based on the transition from the first location to the second location.

17. The method of claim 13, wherein the first location is outside of a moving vehicle and the second location is inside of a moving vehicle, the method further comprising changing a tracking algorithm employed to track the trackee from a first tracking algorithm to a second tracking algorithm based on the transition from the first location to the second location.

18. The method of claim 13, wherein the confidence value is based on one or more confidence values and indicates whether the trackee is indoors, outdoors or in an unknown location.

19. The method of claim 18, wherein each of the one or more confidence values is based on a type of the one or more available sensors.

20. The method of claim 13, wherein the confidence value indicates whether the trackee is traveling by foot or by vehicle, the method further comprising changing a tracking algorithm employed to track the trackee from a first tracking algorithm to a second tracking algorithm based on the transition from the first location to the second location.

21. The method of claim 13, further comprising:

identifying, by the first module, the transition as a landmark;

determining, by a second module, a location estimate that estimates a location of a trackee based on the landmark; and

generating or updating, by the second module, a map including the location.

22. The method of claim 13, wherein the first location is a structured environment and the second location is an unstructured environment, the method further comprising changing a tracking algorithm employed to track the trackee from a first tracking algorithm to a second tracking algorithm based on the transition from the first location to the second location.

23. The method of claim 13, wherein the first location is an unstructured environment and the second location is a structured environment, the method further comprising changing a tracking algorithm employed to track the trackee from a first tracking algorithm to a second tracking algorithm based on the transition from the first location to the second location.

24. 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:

receiving a first signal information, by a first module, from one or more available first sensors among a plurality of first sensors;

determining, by the first module, one or more first confidence values for the first signal information based on a type of the one or more available first sensors;

receiving a second signal information, by the first module, from one or more available second sensors among a plurality of second sensors;

determining, by the first module, one or more second confidence values for the second signal information based on a type of the one or more available second sensors; and

identifying, by the first module, a transition between a first location and a second location based on the first confidence values, the second confidence values, the first signal information, and the second signal information.