On-demand drone noise measurements

• US 10,370,093 B1
• Filed: 11/16/2016
• Issued: 08/06/2019
• Est. Priority Date: 11/16/2016
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Beckman, Brian C., Berlinberg, Eric, Brodie, John Raymond, Buneci, Emilia Sorana
• Primary Examiner(s): Antonucci, Anne M
• Assistant Examiner(s): Stroud, James E
• Application Number:
  US15/353,637
• Time in Patent Office: 993 Days
• Field of Search: 701 3
• CPC Class Codes: B64C 2027/004 using actuators, e.g. active systems
• CPC Class Codes: B64C 27/001 Vibration damping devices
• CPC Class Codes: B64U 10/13 Flying platforms
• CPC Class Codes: B64U 2101/30 for imaging, photography or videography
• CPC Class Codes: B64U 2101/60 for transporting passengers; for transporting goods other than weapons
• CPC Class Codes: B64U 50/19 using electrically powered motors
• CPC Class Codes: G01S 1/751 Mounting or deployment thereof
• CPC Class Codes: G01S 1/753 Signal details
• CPC Class Codes: G08G 5/0021 located in the aircraft
• CPC Class Codes: G08G 5/0034 Assembly of a flight plan
• CPC Class Codes: G08G 5/0069 specially adapted for an unmanned aircraft
• CPC Class Codes: G08G 5/025 Navigation or guidance aids radar or analogous systems specially adapted for landing purposes G01S13/913
• CPC Class Codes: G08G 5/045 Navigation or guidance aids, e.g. determination of anti-collision manoeuvers radar or analogous systems specially adapted for anti-collision between aircraft G01S13/933

Abstract

Techniques for calculating a sound received at a plurality of distances from an unmanned aerial vehicle (UAV) may be provided. For example, during delivery, the UAV may be associated with a sensor to obtain first sound information that corresponds to the sound generated by the UAV. A sensor associated with a landing marker may obtain second sound information about the sound generated by the UAV during flight and delivery of a payload to a location associated with the landing marker. In embodiments, the first sound information and the second sound information may be utilized to calculate sound metrics for the sound generated by the UAV and determine the sound received at a plurality of distances from the UAV during flight.

Claims

1. A computer-implemented method, comprising:

receiving, by a computer system, an order to deliver a payload;

generating, by the computer system, a flight plan that instructs an unmanned aerial vehicle (UAV) to deliver the payload to a location based at least in part on information associated with the order;

receiving, by the computer system, first sound information from a first sensor associated with the UAV, the first sensor configured to obtain sound generated by the UAV during flight;

receiving, by the computer system, second sound information from a second sensor associated with a landing marker of the location, the second sensor configured to obtain the sound generated by the UAV during flight, the landing marker utilized to guide the UAV to deliver the payload;

extracting, by the computer system, sound metrics for the sound generated by the UAV based at least in part on the first sound information and the second sound information;

determining, by the computer system, one or more sound pressure levels for a plurality of distances from the UAV based at least in part on the extracted sound metrics, a sound pressure level of the one or more sound pressure levels identifying the sound received at a particular distance from the UAV during flight; and

instructing, by the computer system, the UAV to alter a modulation of an associated set of propellers based at least in part on the one or more sound pressure levels for the plurality of distances thereby altering the sound generated by the UAV.

2. The computer-implemented method of claim 1, wherein receiving the second sound information is based at least in part on a signal received by the second sensor associated with the landing marker, the signal being provided by the UAV.

3. The computer-implemented method of claim 1, wherein receiving the first sound information from the first sensor associated with the UAV is based at least in part on a first geographic location for the UAV and a second geographic location for the location.

4. The computer-implemented method of claim 1, further comprising identifying a component failure of the UAV based at least in part on the first sound information and the second sound information.

5. The computer-implemented method of claim 1, further comprising:

requesting, by the computer system and from a user device associated with the location, for third sound information obtained by the user device about the sound generated by the UAV; and

updating, by the computer system, the sound metrics for the sound generated by the UAV based at least in part on the third sound information.

6. The computer-implemented method of claim 1, further comprising:

receiving, by the computer system, environmental input within a certain distance of the UAV, the environmental input obtained by a third sensor associated with the UAV; and

updating, by the computer system, the sound metrics for the sound generated by the UAV based at least in part on the environmental input.

7. The computer-implemented method of claim 1, wherein the UAV is configured to store the first sound information in a local data store and transmit the first sound information to the computer system upon arriving at an origination location.

8. A computer-implemented method, comprising:

generating, by a computer system, a flight plan that instructs a first unmanned aerial vehicle (UAV) to land at a location;

receiving, by the computer system, first sound information from a first sensor associated with the first UAV, the first sensor configured to obtain sound generated by the UAV during flight;

receiving, by the computer system, second sound information from a second sensor associated with a second UAV, the second sound information transmitted by the second UAV to the computer system based at least in part on a certain distance between the first UAV and the second UAV during simultaneous flight of the first UAV and the second UAV;

extracting, by the computer system, sound metrics for the sound generated by the first UAV based at least in part on the first sound information and the second sound information; and

generating, by the computer system, a sound map for the location based at least in part on the extracted sound metrics, the sound map identifying sound parameters comprising transformations of the sound calculated for different distances from the first UAV.

9. The computer-implemented method of claim 8, wherein the sound metrics for the sound generated by the first UAV comprise one or more of a sound pressure level for the sound, a sound power level for the sound, a decibel level for the sound, a loudness level for the sound, a sharpness level for the sound, a roughness level for the sound, a tonal prominence for the sound, or a fluctuation strength of the sound.

10. The computer-implemented method of claim 8, wherein the sound map is generated further based at least in part on a machine learning algorithm utilizing the extracted sound metrics.

11. The computer-implemented method of claim 8, further comprising:

configuring the first UAV to utilize a third sensor for obtaining object detection information; and

updating, by the computer system, the object detection information utilizing the first sound information and the second sound information.

12. The computer-implemented method of claim 11, wherein the third sensor includes a time of flight sensor.

13. The computer-implemented method of claim 11, further comprising:

generating, by the computer system, a new flight plan that instructs the first UAV to avoid an object, the object identified using the updated object detection information.

14. The computer-implemented method of claim 8, further comprising updating, by the computer system, the flight plan for the UAV for subsequent flights to the location, the flight plan updated based at least in part on the generated sound map.

15. An unmanned aerial vehicle (UAV), comprising:

a frame;

a set of propellers associated with a propulsion system associated with the frame, the set of propellers configured to provide propulsion for the UAV;

a first sound sensor configured to obtain sound generated by the UAV during flight; and

a computing system configured to manage the propulsion system during a flight associated with a transfer of a payload and further configured to;

obtain, by the first sound sensor, first sound information about the sound generated by the UAV;

receive, from a second sound sensor associated with a landing marker in a first position of a location for the UAV, second sound information;

extract sound metrics for the sound generated by the UAV based at least in part on the first information and the second information; and

transmit, to a user device, instructions for moving the landing marker to a second position of the location based at least in part on the extracted sound metrics.

16. The UAV of claim 15, wherein the computing system is further configured to maintain information that identifies a particular sound level for the location.

17. The UAV of claim 16, wherein the computing system is further configured to alter modulation of the set of propellers based at least in part on the extracted sound metrics and the information thereby altering the sound made by the UAV.

18. The UAV of claim 15, wherein the computing system is further configured to generate a sound map for the location based at least in part on the extracted sound metrics for the sound, the sound map identifying sound parameters comprising transformations of the sound calculated for different distances from the UAV.

19. The UAV of claim 18, wherein the instructions for moving the landing marker to a second position of the location is based at least in part on the generated sound map.

20. The UAV of claim 19, wherein the computing system is further configured to generate a flight plan for subsequent flights to the location based at least in part on the generated sound map.