Cognitive testing, debugging, and remediation of drone

• US 10,553,045 B2
• Filed: 03/01/2018
• Issued: 02/04/2020
• Est. Priority Date: 03/01/2018
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kundu, Ashish, Mahindru, Ruchi, Salapura, Valentina, Singh, Manas R. Kumar
• Primary Examiner(s): Marc-Coleman, Marthe Y
• Application Number:
  US15/909,728
• Publication Number:
  US 20190272686A1
• Time in Patent Office: 705 Days
• Field of Search: 701 3
• CPC Class Codes: B64U 2101/26 for manufacturing, inspections or repairs
• CPC Class Codes: G05B 23/0221 Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
• CPC Class Codes: G05B 23/0297 Reconfiguration of monitoring system, e.g. use of virtual sensors; change monitoring method as a response to monitoring results
• CPC Class Codes: G07C 5/0808 Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005

Abstract

A computer-implemented method includes obtaining fault information regarding a fault associated with a first drone. The computer-implemented method additionally includes obtaining context parameter data of the first drone. The computer-implemented method additionally includes, responsive to obtaining the fault information and the context parameter data, determining to apply a first test case of a plurality of test cases based on a first risk value determined for the first test case using the context parameter data. The first test case is associated with the fault. The computer-implemented method additionally includes causing the first drone to initiate execution of the first test case.

Claims

1. A computer-implemented method, comprising:

obtaining fault information regarding a fault associated with a first drone;

obtaining context parameter data of the first drone;

determining, by a processor, a test plan based on the fault information, wherein the test plan comprises a plurality of test cases including a first test case and a second test case;

determining a first risk value associated with the first test case of the test plan using the context parameter data;

determining a second risk value associated with the second test case of the test plan using the context parameter data;

comparing the first risk value to the second risk value;

determining to initiate execution of the first test case of the test plan when the first risk value is less than the second risk value;

causing the first drone to initiate collection of test data by causing the first drone to initiate execution of the first test case;

determining, based on the test data, a problem with the first drone to obtain an identified problem with the first drone, wherein the identified problem with the first drone corresponds to a cause of the fault;

determining a remediation action for the first drone to perform based on the identified problem; and

causing the first drone to execute the remediation action.

2. The computer-implemented method of claim 1, wherein the context parameter data includes drone traffic in an area in which the first drone is flying.

3. The computer-implemented method of claim 1, wherein the context parameter data includes a current condition of one or more components of the first drone.

4. The computer-implemented method of claim 1, wherein the first risk value is further determined based on results of application of the first test case to one or more second drones.

5. The computer-implemented method of claim 1, wherein the first risk value is determined using known issues associated with the first test case.

6. The computer-implemented method of claim 1, wherein the first risk value is further determined using results of application, to the first drone, of one or more other test cases in the test plan.

7. The computer-implemented method of claim 1, wherein the first test case comprises a test script or a code unit containing test data, and further comprising generating a third test case based on the test data.

8. A system, comprising:

a fault monitoring system configured to obtain fault information regarding a fault associated with a first drone; and

a test and debug system coupled to the fault monitoring system and configured to;

obtain context parameter data of the first drone;

determine a test plan based on the fault information, wherein the test plan comprises a plurality of test cases including a first test case and a second test case;

determine a first risk value associated with the first test case of the test plan using the context parameter data;

determine a second risk value associated with the second test case of the test plan using the context parameter data;

compare the first risk value to the second risk value;

determine to initiate execution of the first test case when the first risk value is less than the second risk value;

cause the first drone to collect test data by causing the first drone to initiate execution of the first test case; and

determine, based on the test data, a problem with the first drone to obtain an identified problem with the first drone, wherein the identified problem with the first drone corresponds to a cause of the fault; and

a remediation action selector configured to;

receive the test data and information indicating the identified problem with the first drone; and

determine a remediation action for the first drone to perform using the identified problem with the first drone.

9. The system according to claim 8, wherein the context parameter data includes weather conditions in an area in which the first drone is flying, landscape in the area, wind speed in the area, drone traffic in the area, or a combination thereof.

10. The system according to claim 8, wherein the context parameter data includes a current condition of one or more components of the first drone.

11. The system according to claim 8, wherein the first risk value is further determined based on results of application of the first test case to one or more second drones.

12. The system according to claim 8, further comprising a test case generator configured to generate a third test case based on the test data.

13. The system according to claim 8, wherein the remediation action is determined from a plurality of remediation options.

14. The system according to claim 13, wherein the remediation options include deploying one or more backup drones, rolling back affected software to a previous version of software, pushing a software upgrade, applying a patch, or a combination thereof.

15. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to:

obtain fault information regarding a fault associated with a first drone;

obtain context parameter data of the first drone;

determine, by the computer, a test plan based on the fault information, wherein the test plan comprises a plurality of test cases including a first test case and a second test case;

determine a first risk value associated with the first test case using the context parameter data;

determine a second risk value associated with the second test case using the context parameter data;

compare the first risk value to the second risk value;

determine to initiate execution of the first test case when the first risk value is less than the second risk value;

cause the first drone to initiate collection of test data by causing the first drone to initiate execution of the first test case;

determine, based on the test data, a problem with the first drone to obtain an identified problem with the first drone, wherein the identified problem with the first drone corresponds to a cause of the fault; and

determine a remediation action for the first drone to perform based on the identified problem.

16. The computer program product of claim 15, wherein the context parameter data includes weather conditions in an area in which the first drone is flying, landscape in the area, wind speed in the area, drone traffic in the area, or a combination thereof.

17. The computer program product according to claim 15, wherein the context parameter data includes a current condition of one or more components of the first drone.

18. The computer program product according to claim 15, wherein the first risk value is further determined based on results of application of the first test case to one or more second drones.

19. The computer program product according to claim 15, wherein the first risk value is determined using known issues associated with the first test case.

20. The computer program product according to claim 15, wherein the first risk value is further determined using results of application, to the first drone, of one or more other test cases in the test plan.