SYSTEMS AND METHODS FOR ADAPTIVE PROPERTY ANALYSIS VIA AUTONOMOUS VEHICLES

• US 20180130196A1
• Filed: 03/01/2017
• Published: 05/10/2018
• Est. Priority Date: 11/04/2016
• Status: Active Grant

• Current Assignee: Loveland Innovations, Inc.
• Original Assignee: Loveland Innovations, LLC
• Inventors: Loveland, Jim, Larson, Leif, Christiansen, Dan, Christiansen, Tad, Christiansen, Cam
• Granted Patent: US 10,055,831 B2
• Time in Patent Office: Days
• CPC Class Codes: B64C 39/024 of the remote controlled vehicle type, i.e. RPV
• CPC Class Codes: B64D 47/08 Arrangements of cameras
• CPC Class Codes: B64U 10/13 Flying platforms
• CPC Class Codes: B64U 2101/30 for imaging, photography or videography
• CPC Class Codes: G01C 11/02 Picture taking arrangements specially adapted for photogrammetry or photographic surveying, e.g. controlling overlapping of pictures
• CPC Class Codes: G05D 1/0044 by providing the operator with a computer generated representation of the environment of the vehicle, e.g. virtual reality, maps maps used for automatic navigation G05D1/0274; flight directors G01C23/005
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/0094 involving pointing a payload, e.g. camera, weapon, sensor, towards a fixed or moving target
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06T 2207/10032 Satellite or aerial image; Remote sensing
• CPC Class Codes: G06T 2207/20101 Interactive definition of point of interest, landmark or seed
• CPC Class Codes: G06T 2207/20104 Interactive definition of region of interest [ROI]
• CPC Class Codes: G06T 2207/30108 Industrial image inspection
• CPC Class Codes: G06T 2207/30184 Infrastructure
• CPC Class Codes: G06T 7/0004 Industrial image inspection
• CPC Class Codes: G06T 7/30 Determination of transform parameters for the alignment of images, i.e. image registration
• CPC Class Codes: G06T 7/38 Registration of image sequences
• CPC Class Codes: G06V 20/176 Urban or other man-made structures
• CPC Class Codes: H04N 1/00204 with a digital computer or a digital computer system, e.g. an internet server programmed control between transmitter and receiver or between image input and image output device H04N1/32561
• CPC Class Codes: H04N 23/45 for generating image signals from two or more image sensors being of different type or operating in different modes, e.g. with a CMOS sensor for moving images in combination with a charge-coupled device [CCD] for still images
• CPC Class Codes: H04N 23/62 : Control of parameters via user interfaces
• CPC Class Codes: H04N 23/66 : Remote control of cameras or camera parts, e.g. by remote control devices
• CPC Class Codes: H04N 7/185 : from a mobile camera, e.g. for remote control

Abstract

An unmanned autonomous vehicle (aerial or ground) assessment and reporting system may conduct micro scans of interior portions of a structure, such as walls, windows, doorways, stairs, and the like. Scan data from one or more sensor types may be compared with stored profile data from a library of profiles using computer vision or other matching techniques to identify characteristics, defects, damage, construction materials, etc. An adaptive response system may modify the types of sensors used for scanning and/or the scanning pattern itself based on matched profile data. Modifications to the scanning process are implemented in real-time based on identified characteristics of the interior portions of the structure.

Claims

1. An unmanned autonomous vehicle assessment system for scanning interior boundaries of a structure from within the structure, comprising:

at least one sensor on an unmanned autonomous vehicle to capture scan data during a detailed micro scan of interior boundaries of a structure that includes a detailed micro scan of an interior doorway leading from a first interior room to a second interior room;

a processor to create an interior planview map of at least a portion of the interior of the structure during the detailed microscan of the interior boundaries of the structure,.

wherein the interior planview map includes the interior boundaries, including the interior doorway;

a non-transitory medium to store the interior planview map;

a library of data profiles corresponding to a sensor type of the at least one sensor; and

an evaluator module to;

compare scan data of the interior doorway captured by the at least one sensor with at least one of a plurality of data profiles stored within the library of data profiles accessible to the unmanned autonomous vehicle assessment system during the detailed micro scan;

identify a stored data profile that matches the scan data, the stored data profile identifying a characteristic of the interior doorway from which the scan data was captured;

determine at least one adaptive scan action to be performed by the unmanned autonomous vehicle in response to the identified characteristic of the interior doorway; and

determine at least one adaptive navigation action to be performed within the structure based on the interior doorway included in the interior a planview map.

3. The unmanned autonomous vehicle assessment system of claim 1, wherein the identified characteristic comprises a construction material identification of the interior doorway.

4. The unmanned autonomous vehicle assessment system of claim 1, wherein the identified characteristic comprises a defect in construction of the interior doorway.

5. The unmanned autonomous vehicle assessment system of claim 1, wherein the identified characteristic comprises at least one of:

water-damage, paint damage, insect damage, and structural damage.

6. The unmanned autonomous vehicle assessment system of claim 1, wherein the identified characteristic comprises damage to the interior doorway.

7. The unmanned autonomous vehicle assessment system of claim 1, wherein the at least one sensor comprises at least one optical imaging sensor and at least one of an infrared imaging sensor and an ultrasonic imaging sensor.

8. The autonomous vehicle assessment system of claim 1, wherein the autonomous vehicle comprises at least one of an unmanned aerial vehicle and an unmanned ground vehicle.

11. The unmanned autonomous vehicle assessment system of claim 1, wherein the at least one sensor comprises an infrared imaging sensor.

12. The unmanned autonomous vehicle assessment system of claim 1, further comprising a navigation system that instructs the unmanned autonomous vehicle to maintain an approximately fixed distance from a surface proximate the interior doorway during a boustrophedonic navigation of the surface proximate the interior doorway of the interior boundary of the structure.

16. The unmanned autonomous vehicle assessment system of claim 1, wherein the interior boundary comprises a ceiling.

2. (canceled)

9. (canceled)

10. (canceled)

13. (canceled)

14. (canceled)

15. (canceled)

17-20. -20. (canceled)

21. A method of scanning an interior boundary of a structure via an unmanned autonomous vehicle assessment system, comprising:

capturing, via a sensor system on an unmanned autonomous vehicle, scan data during an initial detailed micro scan of an interior boundary of a structure from within the structure;

comparing, via processor, scan data of a portion of the interior boundary captured by the sensor with;

at least one of a plurality of data profiles stored within a library of data profiles accessible to the unmanned autonomous vehicle assessment system during the detailed micro scan, and

a stored interior planview map of at least a portion of the structure that includes a plurality of interior walls separating each of a plurality of interior rooms;

identifying a boundary discrepancy in the stored interior planview map based on the scan data, wherein the boundary discrepancy pertains to a discrepancy in one of the interior walls separating the plurality of interior rooms;

annotating the stored interior planview map based on the identified boundary discrepancy with an indication of one of (i) an interior wall to be added to the interior planview map, (ii) an interior wall to be removed from the planview map, and (iii) an interior wall to be modified on the planview map; and

determining at least one adaptive scan action to be performed by the unmanned autonomous vehicle in response to the identified boundary discrepancy. 22-26. (canceled)