VELOCITY CONTROL FOR AN UNMANNED AERIAL VEHICLE

• US 20160070264A1
• Filed: 07/16/2015
• Published: 03/10/2016
• 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: Hu, Xiao, Liu, Ang, Zhou, Guyue, Pan, Xuyang
• Granted Patent: US 9,625,907 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B64C 39/024 of the remote controlled vehicle type, i.e. RPV
• 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 2201/20 Remote controls
• CPC Class Codes: G05D 1/0011 associated with a remote control arrangement
• 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 1/042 specially adapted for aircraft
• CPC Class Codes: G05D 1/102 specially adapted for vertical take-off of aircraft
• CPC Class Codes: G05D 13/00 Control of linear speed; Control of angular speed; Control of acceleration or deceleration, e.g. of a prime mover
• CPC Class Codes: G08G 5/0069 specially adapted for an unmanned aircraft
• CPC Class Codes: G08G 5/04 Anti-collision systems
• 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 on the unmanned aerial vehicle and configured to receive sensor data of the environment and one or more processors. The one or more processors may be individually or collectively configured to: determine, based on the sensor data, an environmental complexity factor representative of an obstacle density for the environment; determine, based on the environmental complexity factor, one or more operating rules for the unmanned aerial vehicle; receive a signal indicating a desired movement of the unmanned aerial vehicle; and cause the unmanned aerial vehicle to move in accordance with the signal while complying with the one or more operating rules.

Claims

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

one or more sensors carried on the unmanned aerial vehicle and configured to receive sensor data of the environment; and

one or more processors individually or collectively configured to;

determine, based on the sensor data, an environmental complexity factor representative of an obstacle density for the environment,

determine, based on the environmental complexity factor, one or more operating rules for the unmanned aerial vehicle,

receive a signal indicating a desired movement of the unmanned aerial vehicle, and

cause the unmanned aerial vehicle to move in accordance with the signal while complying with the one or more operating rules.

2. The system of claim 1, wherein the one or more sensors comprise at least one of the following:

a vision sensor, a lidar sensor, or an ultrasonic sensor.

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

4. The system of claim 1, wherein the sensor data is indicative of an obstacle density for the environment.

5. The system of claim 1, wherein the environmental complexity factor is determined based on a three-dimensional digital representation of the environment generated using the sensor data.

6. The system of claim 5, wherein the three-dimensional digital representation comprises a three-dimensional point cloud or an occupancy grid.

7. The system of claim 1, wherein the one or more operating rules are determined based on previously obtained flight data.

8. The system of claim 1, wherein the one or more operating rules are configured to reduce collisions between the unmanned aerial vehicle and obstacles in the environment.

9. The system of claim 1, wherein the one or more operating rules comprise one or more velocity rules.

10. The system of claim 8, wherein the one or more velocity rules are determined using a first-in-first-out (FIFO) queue of previously determined velocity rules.

11. The system of claim 8, wherein the one or more velocity rules comprise a velocity limit for the unmanned aerial vehicle.

12. The system of claim 8, wherein the one or more velocity rules are determined based on a minimum braking distance for the unmanned aerial vehicle.

13. The system of claim 1, wherein the one or more operating rules comprise one or more altitude rules.

14. The system of claim 1, wherein the one or more operating rules comprise one or more velocity rules.

15. The system of claim 1, wherein the signal comprises a user input command.

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

receiving sensor data of the environment from one or more sensors carried on the unmanned aerial vehicle;

determining, based on the sensor data and with aid of a processor, an environmental complexity factor representative of an obstacle density for the environment;

determining, based on the environmental complexity factor and with aid of the processor, one or more operating rules for the unmanned aerial vehicle;

receiving a signal indicating a desired movement of the unmanned aerial vehicle; and

causing the unmanned aerial vehicle to move in accordance with the signal while complying with the one or more operating rules.

17. The method of claim 16, wherein the one or more sensors comprise at least one of the following:

a vision sensor, a lidar sensor, or an ultrasonic sensor.

18. The method of claim 16, wherein the one or more sensors comprise a plurality of different sensor types.

19. The method of claim 16, wherein the sensor data is indicative of an obstacle density for the environment.

20. The method of claim 16, wherein the environmental complexity factor is determined based on a three-dimensional digital representation of the environment generated using the sensor data.

21. The method of claim 20, wherein the three-dimensional digital representation comprises a three-dimensional point cloud or an occupancy grid.

22. The method of claim 16, wherein the one or more operating rules are determined based on previously obtained flight data.

23. The method of claim 16, wherein the one or more operating rules are configured to reduce collisions between the unmanned aerial vehicle and obstacles in the environment.

24. The method of claim 16, wherein the one or more operating rules comprise one or more velocity rules.

25. The method of claim 24, wherein the one or more velocity rules are determined using a first-in-first-out (FIFO) queue of previously determined velocity rules.

26. The method of claim 24, wherein the one or more velocity rules comprise a velocity limit for the unmanned aerial vehicle.

27. The method of claim 24, wherein the one or more velocity rules are determined based on a minimum braking distance for the unmanned aerial vehicle.

28. The method of claim 16, wherein the one or more operating rules comprise one or more altitude rules.

29. The method of claim 16, wherein the one or more operating rules comprise one or more velocity rules.

30. The method of claim 16, wherein the signal comprises a user input command.