Context-based flight mode selection

• US 9,592,911 B2
• Filed: 07/16/2015
• Issued: 03/14/2017
• Est. Priority Date: 09/05/2014
• Status: Active Grant

• Current Assignee: SZ DJI Technology Co., Ltd. (d/b/a DJI) (iFlight Technology Company Limited)
• Original Assignee: SZ DJI Technology Co., Ltd. (d/b/a DJI) (iFlight Technology Company Limited)
• Inventors: Liu, Ang, Hu, Xiao, Zhou, Guyue, Pan, Xuyang
• Primary Examiner(s): Davis, Richard G
• Application Number:
  US14/801,640
• Publication Number:
  US 20160068267A1
• Time in Patent Office: 607 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: B64C 19/00 Aircraft control not otherwise provided for
• CPC Class Codes: B64U 2101/30 for imaging, photography or videography
• CPC Class Codes: B64U 2201/10 autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS]
• CPC Class Codes: B64U 2201/104 using satellite radio beacon positioning systems, e.g. GPS
• CPC Class Codes: B64U 2201/20 Remote controls
• CPC Class Codes: G05D 1/0061 for transition from automatic pilot to manual pilot and vice versa
• 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 1/0202 specially adapted to aircraft
• CPC Class Codes: G05D 1/042 specially adapted for aircraft
• 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

Systems and methods for controlling an unmanned aerial vehicle within an environment are provided. In one aspect, a system comprises one or more sensors carried by the unmanned aerial vehicle and configured to provide sensor data and one or more processors. The one or more processors can be individually or collectively configured to: determine, based on the sensor data, an environment type for the environment; select a flight mode from a plurality of different flight modes based on the environment type, wherein each of the plurality of different flight mode is associated with a different set of operating rules for the unmanned aerial vehicle; and cause the unmanned aerial vehicle to operate within the environment while conforming to the set of operating rules of the selected flight mode.

Claims

1. A system for controlling an unmanned aerial vehicle within an environment, the system comprising:

one or more processors individually or collectively configured to;

identify an environment type from a plurality of different environment types including an indoor environment, an outdoor environment, a high obstacle density environment, and a low obstacle density environment, based on one or more different types of sensor data generated by one or more different types of sensors,

select a flight mode from a plurality of different flight modes based on the identified environment type, wherein each of the plurality of different flight modes is associated with a distinct set of operating rules for the unmanned aerial vehicle to operate in a different environment type, and

cause the unmanned aerial vehicle to operate within the identified environment type while conforming to the set of operating rules of the selected flight mode.

2. The system of claim 1, wherein the environment type is identified from the plurality of different environment types based on an amount of structures surrounding the unmanned aerial vehicle.

3. The system of claim 1, wherein the one or more different types of sensors comprise one or more of:

a GPS sensor, an inertial sensor, a vision sensor, a lidar sensor, an ultrasonic sensor, a barometer, or an altimeter.

4. The system of claim 1, wherein the one or more different types of sensors comprise a GPS sensor and the environment type is identified based on a number of GPS satellites in communication with the GPS sensor.

5. The system of claim 1, wherein the one or more different types of sensors comprise a lidar sensor and the environment type is identified based on time-of-flight data obtained by the lidar sensor.

6. The system of claim 1, wherein the one or more different types of sensors comprise a vision sensor and the environment type is identified based on image data obtained by the vision sensor.

7. The system of claim 6, wherein the environment type is identified based on an exposure time associated with the image data obtained by the vision sensor.

8. The system of claim 1, wherein the plurality of different flight modes comprises two or more of:

an indoor flight mode, an outdoor flight mode, a high altitude flight mode, a low altitude flight mode, a fully autonomous flight mode, a semi-autonomous flight mode, or a manual flight mode.

9. The system of claim 1, wherein each distinct set of operating rules comprises different processing rules for processing data obtained by the one or more different types of sensors.

10. The system of claim 9, wherein the different processing rules define different methods for fusing the data obtained by the one or more different types of sensors.

11. The system of claim 1, wherein each distinct set of operating rules comprises different control rules for controlling flight of the unmanned aerial vehicle.

12. The system of claim 11, wherein the different control rules define different obstacle avoidance strategies for the unmanned aerial vehicle.

13. The system of claim 1, wherein at least one flight mode comprises a distinct set of operating rules that permits the one or more processors to override an input from a user.

14. A method of controlling an unmanned aerial vehicle within an environment, the method comprising:

receiving one or more different types of sensor data from one or more different types of sensors carried by the unmanned aerial vehicle;

identifying an environment type from a plurality of different environment types including an indoor environment, an outdoor environment, a high obstacle density environment, and a low obstacle density environment based on the one or more different types of sensor data;

selecting a flight mode from a plurality of different flight modes based on the identified environment type, wherein each of the plurality of different flight modes is associated with a distinct set of operating rules for the unmanned aerial vehicle to operate in a different environment type; and

causing the unmanned aerial vehicle to operate within the identified environment type while conforming to the set of operating rules of the selected flight mode.

15. The method of claim 14, wherein the environment type is identified from the plurality of different environment types based on an amount of structures surrounding the unmanned aerial vehicle.

16. The method of claim 14, wherein each distinct set of operating rules comprises different control rules for controlling flight of the unmanned aerial vehicle, the different control rules defining different obstacle avoidance strategies for the unmanned aerial vehicle.

17. A system for controlling an unmanned aerial vehicle, the system comprising:

one or more different types of sensors carried by the unmanned aerial vehicle; and

one or more processors individually or collectively configured to;

identify a first environment type from a plurality of different environment types including an indoor environment, an outdoor environment, a high obstacle density environment, and a low obstacle density environment, based on one or more different types of sensor data generated by the one or more different types of sensors,

select a first flight mode from a plurality of different flight modes based on the identified first environment type, wherein each of the plurality of different flight modes is associated with a distinct set of operating rules for the unmanned aerial vehicle to operate in a different environment type,

cause the unmanned aerial vehicle to operate within the identified first environment type while conforming to the set of operating rules of the first flight mode,

identify a second environment type from the plurality of different environment types based on one or more different types of sensor data generated by the one or more different types of sensors,

select a second flight mode from the plurality of different flight modes based on the identified second environment type, and

cause the unmanned aerial vehicle to operate within the identified second environment type while conforming to the set of operating rules of the second flight mode.

18. The system of claim 17, wherein the first and second environment types are identified from the plurality of different environment types based on an amount of structures surrounding the unmanned aerial vehicle.

19. The system of claim 17, wherein the one or more different types of sensors comprise one or more of:

a GPS sensor, an inertial sensor, a vision sensor, a lidar sensor, an ultrasonic sensor, a barometer, or an altimeter.

20. The system of claim 17, wherein the one or more different types of sensors comprise a GPS sensor and the first and second environment types are identified based on a number of GPS satellites in communication with the GPS sensor.

21. The system of claim 17, wherein the one or more different types of sensors comprise a lidar sensor and the first and second environment types are identified based on time-of-flight data obtained by the lidar sensor.

22. The system of claim 17, wherein the one or more different types of sensors comprise a vision sensor and the first and second environment types are identified based on image data obtained by the vision sensor.

23. The system of claim 22, wherein the first and second environment types are identified based on an exposure time associated with the image data obtained by the vision sensor.

24. The system of claim 17, wherein the plurality of different flight modes comprises two or more of:

an indoor flight mode, an outdoor flight mode, a high altitude flight mode, a low altitude flight mode, a fully autonomous flight mode, a semi-autonomous flight mode, or a manual flight mode.

25. The system of claim 17, wherein each distinct set of operating rules comprises different control rules for controlling flight of the unmanned aerial vehicle.

26. The system of claim 25, wherein the different control rules comprise different obstacle avoidance strategies for the unmanned aerial vehicle.

27. The system of claim 17, wherein at least one flight mode comprises a distinct set of operating rules that permits the one or more processors to override an input from a user.

28. A method of controlling an unmanned aerial vehicle, the method comprising:

identifying a first environment type from a plurality of different environment types including an indoor environment, an outdoor environment, a high obstacle density environment, and a low obstacle density environment, based on one or more different types of sensor data generated by the one or more different types of sensors;

selecting a first flight mode from a plurality of different flight modes based on the identified first environment type, wherein each of the plurality of different flight modes is associated with a distinct set of operating rules for the unmanned aerial vehicle to operate in a different environment type;

causing the unmanned aerial vehicle to operate within the identified first environment type while conforming to a first set of operating rules of the first flight mode;

identifying a second environment type from the plurality of different environment types based on one or more different types of sensor data generated by the one or more different types of sensors;

selecting a second flight mode from the plurality of different flight modes based on the identified second environment type and with aid of a processor; and

causing the unmanned aerial vehicle to operate within the identified second environment type while conforming to a second set of operating rules of the second flight mode.

29. The method of claim 28, wherein each distinct set of operating rules comprises different control rules for controlling flight of the unmanned aerial vehicle.

30. The method of claim 29, wherein the different control rules define different obstacle avoidance strategies for the unmanned aerial vehicle.