Indoor positioning system training

• US 10,077,984 B2
• Filed: 09/25/2015
• Issued: 09/18/2018
• Est. Priority Date: 09/25/2015
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Akselrod, Ben Z., DiLoreto, Anthony, McDuff, Steve, Robeson, Kyle D.
• Primary Examiner(s): Cass, Jean Paul
• Application Number:
  US14/864,950
• Publication Number:
  US 20170090477A1
• Time in Patent Office: 1,089 Days
• Field of Search: 701 25
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: G05D 1/0221 involving a learning process
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: G05D 1/028 using a RF signal

Abstract

In an approach for collecting data, a computer identifies a virtual map of an environment. The computer determines a location associated with one or more autonomous devices within the identified virtual map. The computer provides to a first autonomous device of the one or more autonomous devices, navigation instructions from a determined location associated with the first autonomous device to a first training point. The computer collects training data associated with the first training point through the first autonomous device.

Claims

1. A method for collecting data through a flight plan that controls an unmanned aerial vehicle, the method comprising:

identifying, by one or more computer processors, a virtual map of an indoor environment wherein the virtual map is a vector diagram mapping one or more physical features of the indoor environment that includes;

measurements for size, location, a magnitude, and a direction to the one or more physical features within the indoor environment;

determining, by one or more computer processors, a location associated with one or more autonomous devices within the identified virtual map;

providing, by one or more computer processors, to a first autonomous device of the one or more autonomous devices, navigation instructions from the determined location associated with the one or more autonomous devices to a first training point, wherein the first training point is a wireless access point within the indoor environment, wherein the navigation instructions include a flight plan determined by information from an indoor positioning system, wherein the first autonomous device is an unmanned aerial vehicle;

collecting, by one or more computer processors, training data associated with the first training point through the first autonomous device, wherein the training data aids in the calibration of the indoor positioning system;

determining, by one or more computer processors, the first autonomous device reaches the first training point;

responsive to determining the first autonomous device reaches the first training point, receiving, by one or more computer processors, a specified height;

positioning, by one or more computer processors, the first autonomous device based on one of the following;

altering a hover height to the received specified height and raising an antenna to the received specified height;

receiving, by one or more computer processors, an indication that the positioned first autonomous device is in position for training the first training point;

sending, by one or more computer processors, an indication to initiate training of the first training point;

analyzing, by one or more computer processors, the collected training data; and

calibrating, by one or more computer processors, the first training point based on the analyzed training data.

2. The method of claim 1, wherein determining the location associated with the one or more autonomous devices within the received virtual map further comprises:

receiving, by one or more computer processors, data from a first scan of the environment, wherein the received data includes reflections that indicate objects within the scan of the environment;

calculating, by one or more computer processors, a first set of one or more distances and directions of the first autonomous device relative to the objects within the first scan of the environment based on the received reflections; and

comparing, by one or more computer processors, the first set of calculated one or more distances and directions of the first autonomous device relative to objects with one or more distances and directions of the first autonomous device relative to objects associated with the determined location of the first autonomous device within the identified virtual map.

3. The method of claim 1, further comprising:

determining, by one or more computer processors, whether an ambiguity exists in the determined location of the first autonomous device of the one or more autonomous devices within the identified virtual map, wherein the ambiguity identifies at least two determined locations of the first autonomous device;

responsive to determining the ambiguity exists, repositioning, by one or more computer processors, the first autonomous device;

performing, by one or more computer processors, a second scan of the indoor environment;

receiving, by one or more computer processors, data from the second scan of the indoor environment;

calculating, by one or more computer processors, a second set of one or more distances and directions of the first autonomous device based on the received data from the second scan of the indoor environment;

comparing, by one or more computer processors, the second set of calculated one or more distances and directions of the first autonomous device to the at least two determined locations of the first autonomous device associated with the determined ambiguity; and

determining, by one or more computer processors, a location associated with the repositioned first autonomous device within the identified virtual map based on the comparison.

4. The method of claim 1, further comprising:

sending, by one or more computer processors, a received signal strength indicator at a specified level to the first training point from the first autonomous device, wherein the sent received signal strength indicator is a set uniform power level;

collecting, by, one or more computer processors, training data associated with the first training point via the first autonomous device based on the sent received signal strength indicator, wherein the training data includes a measured received signal strength indicator level associated with the first training point; and

determining, by one or more computer processors, whether the collected training data exceeds a defined data threshold that includes one of;

a specific number of data points based on the collected training data, a maximum variation between the sent received signal strength indicator and the received signal strength indicator level associated with the first training point and a minimum variation, and a minimum variation between the sent received signal strength indicator and the received signal strength indicator level associated with the first training point.

5. The method of claim 4, further comprising:

responsive to determining the collected training data exceeds the defined data threshold, identifying, by one or more computer processors, a second training point in which collection of training data has yet to occur.

6. The method of claim 1, wherein the one or more autonomous devices communicate information between the one or more autonomous devices, and wherein the communicated information includes a location associated with each of the one or more autonomous devices, an operational status associated with each of the one or more autonomous devices that identifies one of the following:

an on state, an off state, and a training state, an assigned training point that identifies the wireless access point to be trained by each of the one or more autonomous devices, and training information.

7. A computer program product for collecting data through a flight plan that controls an unmanned aerial vehicle, the computer program product comprising:

one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising;

program instructions to identify a virtual map of an indoor environment wherein the virtual map is a vector diagram mapping one or more physical features of the indoor environment that includes;

measurements for size, location, a magnitude and a direction to the one or more physical features within the indoor environment;

program instructions to determine a location associated with one or more autonomous devices within the identified virtual map;

program instructions to provide to a first autonomous device of the one or more autonomous devices, navigation instructions from the determined location associated with the one or more autonomous devices to a first training point, wherein the first training point is a wireless access point within the indoor environment, wherein the navigation instructions include a flight plan determined by information from an indoor positioning system, wherein the first autonomous device is an unmanned aerial vehicle;

program instructions to collect training data associated with the first training point through the first autonomous device, wherein the training data aids in the calibration of the indoor positioning system;

program instructions to determine the first autonomous device reaches the first training point;

responsive to determining the first autonomous device reaches the first training point, program instructions to receive a specified height;

program instructions to position the first autonomous device based on one of the following;

altering a hover height to the received specified height and raising an antenna to the received specified height;

program instructions to receive an indication that the positioned first autonomous device is in position for training the first training point;

program instructions to send an indication to initiate training of the first training point;

program instructions to analyze the collected training data; and

program instructions to calibrate the first training point based on the analyzed training data.

8. The computer program product of claim 7, wherein to determine the location associated with the one or more autonomous devices within the received virtual map further comprises program instructions, stored on the one or more computer readable storage media, to:

receive data from a first scan of the environment, wherein the received data includes reflections that indicate objects within the scan of the environment;

calculate a first set of one or more distances and directions of the first autonomous device relative to the objects within the first scan of the environment based on the received reflections; and

compare the first set of calculated one or more distances and directions of the first autonomous device relative to objects with one or more distances and directions of the first autonomous device relative to objects associated with the determined location of the first autonomous device within the identified virtual map.

9. The computer program product of claim 7, further comprising program instructions, stored on the one or more computer readable storage media, to:

determine whether an ambiguity exists in the determined location of the first autonomous device of the one or more autonomous devices within the identified virtual map, wherein the ambiguity identifies at least two determined locations of the first autonomous device;

responsive to determining the ambiguity exists, reposition the first autonomous device;

perform a second scan of the indoor environment;

receive data from the second scan of the indoor environment;

calculate a second set of one or more distances and directions of the first autonomous device based on the received data from the second scan of the indoor environment;

compare the second set of calculated one or more distances and directions of the first autonomous device to the at least two determined locations of the first autonomous device associated with the determined ambiguity; and

determine a location associated with the repositioned first autonomous device within the identified virtual map based on the comparison.

10. The computer program product of claim 7, further comprising program instructions, stored on the one or more computer readable storage media, to:

send a received signal strength indicator at a specified level to the first training point from the first autonomous device, wherein the sent received signal strength indicator is a set uniform power level;

collect training data associated with the first training point via the first autonomous device based on the sent received signal strength indicator, wherein the training data includes a measured received signal strength indicator level associated with the first training point; and

determine whether the collected training data exceeds a defined data threshold that includes one of;

a specific number of data points based on the collected training data, a maximum variation between the sent received signal strength indicator and the received signal strength indicator level associated with the first training point and a minimum variation, and a minimum variation between the sent received signal strength indicator and the received signal strength indicator level associated with the first training point.

11. The computer program product of claim 10, further comprising program instructions, stored on the one or more computer readable storage media, to:

responsive to determining the collected training data exceeds the defined data threshold, identify a second training point in which collection of training data has yet to occur.

12. The computer program product of claim 7, wherein the one or more autonomous devices communicate information between the one or more autonomous devices, and wherein the communicated information includes a location associated with each of the one or more autonomous devices, an operational status associated with each of the one or more autonomous devices that identifies one of the following:

an on state, an off state, and a training state, an assigned training point that identifies the wireless access point to be trained by each of the one or more autonomous devices, and training information.

13. A computer system for collecting data through a flight plan that controls an unmanned aerial vehicle, the computer system comprising:

one or more computer processors, one or more computer readable storage media, and program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising;

program instructions to identify a virtual map of an indoor environment wherein the virtual map is a vector diagram mapping one or more physical features of the indoor environment that includes;

measurements for size, location, and a magnitude and a direction to the one or more physical features within the indoor environment;

program instructions to determine a location associated with one or more autonomous devices within the identified virtual map;

program instructions to provide to a first autonomous device of the one or more autonomous devices, navigation instructions from the determined location associated with the one or more autonomous devices to a first training point, wherein the first training point is a wireless access point within the indoor environment, wherein the navigation instructions include a flight plan determined by information from an indoor positioning system, wherein the first autonomous device is an unmanned aerial vehicle;

program instructions to collect training data associated with the first training point through the first autonomous device, wherein the training data aids in the calibration of the indoor positioning system;

program instructions to determine the first autonomous device reaches the first training point;

responsive to determining the first autonomous device reaches the first training point, program instructions to receive a specified height;

program instructions to position the first autonomous device based on one of the following;

altering a hover height to the received specified height and raising an antenna to the received specified height;

program instructions to receive an indication that the positioned first autonomous device is in position for training the first training point;

program instructions to send an indication to initiate training of the first training point;

program instructions to analyze the collected training data; and

program instructions to calibrate the first training point based on the analyzed training data.

14. The computer system of claim 13, wherein to determine the location associated with the one or more autonomous devices within the received virtual map further comprises program instructions, stored on the one or more computer readable storage media, to:

receive data from a first scan of the environment, wherein the received data includes reflections that indicate objects within the scan of the environment;

calculate a first set of one or more distances and directions of the first autonomous device relative to the objects within the first scan of the environment based on the received reflections; and

compare the first set of calculated one or more distances and directions of the first autonomous device relative to objects with one or more distances and directions of the first autonomous device relative to objects associated with the determined location of the first autonomous device within the identified virtual map.

15. The computer system product of claim 13, further comprising program instructions, stored on the one or more computer readable storage media, to:

determine whether an ambiguity exists in the determined location of the first autonomous device of the one or more autonomous devices within the identified virtual map, wherein the ambiguity identifies at least two determined locations of the first autonomous device;

responsive to determining the ambiguity exists, reposition the first autonomous device;

perform a second scan of the indoor environment;

receive data from the second scan of the indoor environment;

calculate a second set of one or more distances and directions of the first autonomous device based on the received data from the second scan of the indoor environment;

compare the second set of calculated one or more distances and directions of the first autonomous device to the at least two determined locations of the first autonomous device associated with the determined ambiguity; and

determine a location associated with the repositioned first autonomous device within the identified virtual map based on the comparison.

16. The computer system of claim 13, further comprising program instructions, stored on the one or more computer readable storage media, to:

send a received signal strength indicator at a specified level to the first training point from the first autonomous device, wherein the sent received signal strength indicator is a set uniform power level;

collect training data associated with the first training point via the first autonomous device based on the sent received signal strength indicator, wherein the training data includes a measured received signal strength indicator level associated with the first training point; and

determine whether the collected training data exceeds a defined data threshold that includes one of;

a specific number of data points based on the collected training data, a maximum variation between the sent received signal strength indicator and the received signal strength indicator level associated with the first training point and a minimum variation, and a minimum variation between the sent received signal strength indicator and the received signal strength indicator level associated with the first training point.