IP Library › Granted Patent US 10,497,108
Granted Patent B1
US 10,497,108 · App. 15/843,983 · Granted Dec 3, 2019

Systems and methods for machine-assisted vehicle inspection

Inventors: Ryan Knuffman (Danvers, IL); Bradley A. Sliz (Normal, IL); Lucas Allen (East Peoria, IL)
Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
G06T7/0004G06N20/00G06Q40/08G07C5/006G06T2207/20081G06T2207/30252
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Quick Facts
Patent No.
US 10,497,108
App. No.
15/843,983
Granted
Dec 3, 2019
Kind
B1
Abstract

One or more processing elements may be trained to identify vehicle damages or vehicle damages based upon training data. A remotely-controlled (RC) and/or autonomously operated inspection device, such as a ground vehicle or drone, may capture one or more sets of imaging data indicative of at least a portion of an automotive vehicle, such as all or a portion of the undercarriage. The one or more sets of imaging data may be analyzed using the trained processing elements to identify a damage to the vehicle or defect of the vehicle.

Claims (30)

1. A computer-implemented method for identifying at least one of damage to a current vehicle or a defect of the current vehicle damage based upon training sets of imaging data indicative of reference vehicles, the method comprising:

training one or more processing elements to identify at least one of vehicle damages or vehicle defects based upon the training sets of imaging data, the training sets of imaging data being indicative of, for each of the reference vehicles, at least a portion of the reference vehicle;

receiving, via a communication element, an indication of a claim associated with a reported at least one of a damage to the current vehicle or defect of the current vehicle;

determining, via the one or more trained processing elements, based upon the claim, at least a portion of the current vehicle of which to capture imaging data;

obtaining, via the communication element, one or more current sets of imaging data captured by an imaging unit of an inspection device that is at least one of autonomously operated or remotely-controlled, each the one or more current sets of imaging data being indicative of the determined at least the portion of the current vehicle; and

analyzing, via the one or more trained processing elements, the one or more current sets of imaging data to identify or verify the at least one of the damage to the current vehicle or the defect of the current vehicle.

2. The computer-implemented method of claim 1 , wherein the inspection device is a ground inspection device that is at least one of autonomously operated or remotely-controlled.

3. The computer-implemented method of claim 1 , wherein the inspection device is an airborne inspection device that is at least one of autonomously operated or remotely-controlled.

4. The computer-implemented method of claim 1 , wherein the identified or verified at least one of the damage or the defect includes at least one of a damaged vehicle part or a defective vehicle part.

5. The computer-implemented method of claim 4 , further comprising scheduling, via the one or more processing elements, at least one of a maintenance, a repair, or a replacement of the at least one of the damaged vehicle part or the defective vehicle part.

6. The computer-implemented method of claim 4 , further comprising identifying, via the one or more processing elements, a replacement part for replacing the at least one of the damaged vehicle part or the defective vehicle part.

7. The computer-implemented method of claim 6 , further comprising initiating, via the one or more processing elements, an order of the replacement part for replacing the at least one of the damaged vehicle part or the defective vehicle part.

8. The computer-implemented method of claim 1 , wherein the identified or verified at least one of the damage or the defect includes an improper wheel alignment.

9. The computer-implemented method of claim 8 , further comprising scheduling, via the one or more processing elements, a maintenance for correcting the improper wheel alignment.

10. A computer system configured to identify at least one of damage to a current vehicle or a defect of the current vehicle based upon training sets of imaging data indicative of reference vehicles, the computer system comprising:

one or more processing elements; and

one or more memories comprising computer-executable instructions that, when executed by the one or more processing elements, cause the computer system to:

train the one or more processing elements to identify at least one of vehicle damages or vehicle defects based upon the training sets of imaging data, the training sets of imaging data being indicative of, for each of the reference vehicles, at least a portion of the reference vehicle;

receive, via a communication element, an indication of a claim associated with a reported at least one of a damage to the current vehicle or defect of the current vehicle;

determine, via the one or more trained processing elements, based upon the claim, at least a portion of the current vehicle of which to capture imaging data;

obtain, via the communication element, one or more current sets of imaging data captured by an imaging unit of an inspection device that is at least one of autonomously operated or remotely-controlled, each the one or more current sets of imaging data being indicative of the determined at least the portion of the current vehicle; and

analyze, via the one or more trained processing elements, the one or more current sets of imaging data to identify or verify the at least one of the damage to the current vehicle or the defect of the current vehicle.

11. The computer system of claim 10 , wherein the one or more current sets of imaging data include one or more sets of thermal imaging data.

12. The computer system of claim 10 , wherein the one or more current sets of imaging data include one or more sets of lidar imaging data.

13. The computer system of claim 10 , wherein the one or more current sets of imaging data include one or more sets of imaging data captured using a wide-angle camera lens of the imaging unit.

14. The computer system of claim 10 , wherein the computer system is further configured to generate, via the one or more processing elements, one or more terms of an insurance policy based upon the identified or verified at least one of the damage or the defect.

15. The computer system of claim 10 , wherein the computer system is further configured to modify, via the one or more processing elements, based upon the identified or verified at least one of the damage or the defect, an insurance policy of a party associated with the current vehicle.

16. The computer-implemented method of claim 15 , wherein modifying the insurance policy includes modifying at least one of a premium, a coverage limit, or a deductible.

17. The computer system of claim 10 , wherein the computer system is further configured to estimate, via the one or more processing elements, a monetary cost of at least one of a maintenance, a service, or a repair for correcting the identified or verified at least one of the damage or the defect.

18. The computer system of claim 10 , wherein the computer system is further configured to transmit, via at least one of the one or more processing elements or the communication element, to at least one of a mobile device of an owner of the current vehicle or a mobile device of an insurance representative, an indication of the identified or verified at least one of the damage or the defect.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 20, 2018
From: KNUFFMAN, RYAN; SLIZ, BRADLEY A.; ALLEN, LUCAS
To: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
Reel/Frame 046139/0456 →
Continuity (1)
Provisional Application 62438769 · Dec 23, 2016
Cited By (11)
US 12,205,266 US 12,211,272 US 12,322,219 US 12,327,445 US 12,367,571 US 12,392,730 US 12,425,747 US 12,541,840 US 12,591,358 US 12,597,114 US 12,597,115