Velocity control for an unmanned aerial vehicle

Patent metadata

Field	Value
Publication number	US-2017052541-A1
Application number	US-201615277455-A
Country	US
Kind code	A1
Filing date	Sep 27, 2016
Priority date	Sep 5, 2014
Publication date	Feb 23, 2017
Grant date	—

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.

First claim

1 . (canceled)

2 . 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 one or more processors individually or collectively configured to:
determine, based on data from the one or more sensors, an environmental complexity factor representative of an obstacle density for the environment,
determine, based on the environmental complexity factor, a first set of operating rules for the unmanned aerial vehicle,
detect, based on data from the one or more sensors, a change in the environmental complexity factor corresponding to a change in the obstacle density for the environment, and
modify the first set of operating rules based on the change in the environmental complexity factor to provide a second set of operating rules for the unmanned aerial vehicle.

3 . The system of claim 2 , wherein the one or more sensors comprise at least one of the following: a vision sensor, a lidar sensor, or an ultrasonic sensor.

4 . The system of claim 2 , wherein the one or more sensors comprise a plurality of different sensor types.

5 . The system of claim 2 , wherein the one or more sensors are configured to receive the data, and wherein the data is indicative of the obstacle density for the environment.

6 . The system of claim 2 , wherein the environmental complexity factor is determined based on a three-dimensional digital representation of the environment generated using the sensor data.

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

8 . The system of claim 2 , wherein the first set of operating rules comprises a first set of velocity rules and the second set of operating rules comprises a second set of velocity rules.

9 . The system of claim 8 , wherein at least one of the first and second sets of velocity rules is determined based on a minimum braking distance for the unmanned aerial vehicle.

10 . The system of claim 8 , wherein the first and second sets of velocity rules each comprise a velocity limit for the unmanned aerial vehicle.

11 . The system of claim 10 , wherein when the change in the environmental complexity factor corresponds to a decrease in the obstacle density, the velocity limit of the second set of velocity rules is greater than the velocity limit of the first set of velocity rules.

12 . A method for controlling an unmanned aerial vehicle within an environment, the method comprising:
receiving, with aid of a processor, sensor data of the environment from one or more sensors carried on the unmanned aerial vehicle; determining, based on the sensor data, 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, a first set of operating rules for the unmanned aerial vehicle, detecting, based on the sensor data, a change in the environmental complexity factor corresponding to a change in the obstacle density for the environment, and modifying the first set of operating rules based on the change in the environmental complexity factor to provide a second set of operating rules for the unmanned aerial vehicle.

13 . The method of claim 12 , wherein the one or more sensors comprise at least one of the following: a vision sensor, a lidar sensor, or an ultrasonic sensor.

14 . The method of claim 12 , wherein the one or more sensors comprise a plurality of different sensor types.

15 . The method of claim 12 , wherein the sensor data is indicative of the obstacle density for the environment.

16 . The method of claim 12 , further comprising the environmental complexity factor is determined based on a three-dimensional digital representation of the environment generated using the sensor data.

17 . The method of claim 16 , wherein the three-dimensional digital representation comprises a three-dimensional point cloud or an occupancy grid.

18 . The method of claim 12 , wherein the first set of operating rules comprises a first set of velocity rules and the second set of operating rules comprises a second set of velocity rules.

19 . The method of claim 18 , wherein at least one of the first and second sets of velocity rules is determined based on a minimum braking distance for the unmanned aerial vehicle.

20 . The method of claim 18 , wherein the first and second sets of velocity rules each comprise a velocity limit for the unmanned aerial vehicle.

21 . The method of claim 20 , wherein when the change in the environmental complexity factor corresponds to a decrease in the obstacle density, the velocity limit of the second set of velocity rules is greater than the velocity limit of the first set of velocity rules.

Assignees

• Sz Dji Technology Co Ltd

Inventors

• Hu Xiao
• Liu Ang
• Zhou Guyue
• Pan Xuyang

Classifications

• B64U2201/20

  Remote controls · CPC title

• B64U2201/10

  autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS] · CPC title

• G05D13/00

  Control of linear speed; Control of angular speed; Control of acceleration or deceleration, e.g. of a prime mover · CPC title

• B64C39/024

  of the remote controlled vehicle type, i.e. RPV · CPC title

• G05D1/0088 Primary

  characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours (using knowledge based models G06N5/00) · CPC title