Autonomous and non-autonomous dynamic model based navigation system for unmanned vehicles

Patent metadata

Field	Value
Publication number	US-9978285-B2
Application number	US-201615176283-A
Country	US
Kind code	B2
Filing date	Jun 8, 2016
Priority date	Jun 10, 2015
Publication date	May 22, 2018
Grant date	May 22, 2018

Abstract

A navigation system including a vehicle dynamic model (VDM) that serves as the main process model within a navigation filter is described. When used in an unmanned aerial vehicle (UAV), the navigation system may work in communication with inertial measurement units (IMUs) and environment dependent sensors such as GNSS receivers. Particularly, the navigation system is beneficial in the case of GNSS signal reception outages, where conventional IMU coasting drifts quickly. Yet, the navigation system may also be employed in other scenarios, for example during GNSS presence for improved positioning, velocity and attitude determination, or in combination with GNSS when no IMU is available by design or due to a failure. In the navigation system, a solution to VDM equations provides an estimate of position, velocity, and attitude, which can be updated within a navigation filter based on available observations, such as IMU data or GNSS measurements.

First claim

What is claimed is:

1. A navigation platform for autonomous and non-autonomous navigation of an unmanned aerial vehicle, comprising:
an inertial measurement unit providing inertial measurements data;
a global navigation satellite system device providing at least one of position measurement data, velocity measurement data, or receiver to satellite distance related measurements;
at least one of an autopilot or a manual control device providing data of control input to actuators of the unmanned aerial vehicle; and
a navigation system including:
a self-calibrating vehicle dynamic model component providing linear and rotational accelerations of the unmanned aerial vehicle utilizing control input and previously estimated velocity and attitude, and
a navigation filter using the vehicle dynamic model component as a main navigation process model for navigation of the unmanned aerial vehicle, the navigation filter receiving the data of control input to actuators of the unmanned aerial vehicle from the autopilot or the manual control device, the navigation filter receiving the inertial navigation data from the inertial measurement unit and updating an output of the vehicle dynamic model component with at least a portion of the inertial navigation data, the navigation filter receiving the at least one of position or velocity measurement data from the global navigation satellite system device when available and updating the output of the vehicle dynamic model component with the at least one of position or velocity measurement data when available, the navigation filter estimating position, velocity, attitude, and attitude rates of the unmanned aerial vehicle, the navigation filter estimating vehicle dynamic model parameters to calibrate the vehicle dynamic model component, the navigation filter estimating a wind velocity vector to provide the wind velocity to the vehicle dynamic model component, and the navigation filter estimating and compensating for errors in the inertial measurement unit.

2. The navigation platform of claim 1 , further comprising at least one autonomous aiding device that provides navigation related data and wherein the navigation filter receives the navigation related data from the at least one autonomous aiding device and updates the output of the vehicle dynamic model component with at least a portion of the navigation related data.

3. The navigation platform of claim 1 , further comprising at least one environment dependent aiding device that provides navigation related data, and wherein the navigation filter receives the navigation related data from the at least one environment dependent aiding device and updates the output of the vehicle dynamic model component with at least a portion of the navigation related data.

4. The navigation platform of claim 2 , wherein the at least one autonomous aiding device includes at least one of a barometric altimeter, a magnetometer, or a speed sensor.

5. The navigation platform of claim 1 , wherein the navigation system further includes at least one of a wind model and an inertial measurement unit error model, and wherein the navigation filter estimates the wind velocity using data provided by at least one of the wind model and the inertial measurement unit error model.

6. The navigation platform of claim 3 , wherein the at least one environment dependent aiding device includes at least one of a radio frequency ranging device, a vision based sensor, an ultrasound sensor, or an optical flow sensor.

7. The navigation platform of claim 1 , wherein the unmanned aerial vehicle is selected from the group consisting of a fixed-wing unmanned aerial vehicle and a rotary-wing unmanned aerial vehicle.

8. A navigation platform for autonomous and non-autonomous navigation of an unmanned aerial vehicle, comprising:
an inertial measurement unit providing inertial navigation data;
at least one of an autopilot or a manual control device providing data of control input to actuators of the unmanned aerial vehicle; and
a navigation system including:
a self-calibrating vehicle dynamic model component providing linear and rotational accelerations of the unmanned aerial vehicle utilizing control input and previously estimated velocity and attitude, and
a navigation filter using the vehicle dynamic model component as a main navigation process model for navigation of the unmanned aerial vehicle, the navigation filter receiving the data of control input to actuators of the unmanned aerial vehicle from at least one of the autopilot or the manual control device, the navigation filter receiving the inertial navigation data from the inertial measurement unit and updating an output of the vehicle dynamic model component with at least a portion of the inertial navigation data, the navigation filter estimating position, velocity, attitude, and attitude rates of the unmanned aerial vehicle, the navigation filter estimating vehicle dynamic model parameters to calibrate the vehicle dynamic model component, the navigation filter estimating a wind velocity vector to provide the wind velocity to the vehicle dynamic model component, and the navigation filter estimating and compensating for errors in the inertial measurement unit.

9. The navigation platform of claim 8 , further comprising at least one autonomous aiding device that provides navigation related data, and wherein the navigation filter receives the navigation related data from the at least one autonomous aiding device and updates the output of the vehicle dynamic model component with at least a portion of the navigation related data.

10. The navigation platform of claim 8 , further comprising at least one environment dependent aiding device that provides navigation related data, and wherein the navigation filter receives the navigation related data from the at least one environment dependent aiding device and updates the output of the vehicle dynamic model component with at least a portion of the navigation related data.

11. The navigation platform of claim 9 , wherein the at least one autonomous aiding device includes at least one of a barometric altimeter, a magnetometer, or a speed sensor.

12. The navigation platform of claim 8 , wherein the navigation system further includes at least one of a wind model and an inertial measurement unit error model, and wherein the navigation filter estimates the wind velocity using data provided by at least one of the wind model and the inertial measurement unit error model.

13. The navigation platform of claim 10 , wherein the at least one environment dependent aiding device including at least one of a radio frequency ranging device, a vision based sensor, an ultrasound sensor, or an optical flow sensor.

14. The navigation platform of claim 8 , wherein the unmanned aerial vehicle is selected from the group consisting of a fixed-wing unmanned aerial vehicle and a rotary-wing unmanned aerial vehicle.

15. A navigation platform for autonomous and non-autonomous navigation of an unmanned aerial vehicle, comprising:
a global navigation satellite system device providing at least one of position measurement data, velocity measurement data, or receiver to satellite distance related measurements;
at least one of an autopilot or a manual control device providing data of control input to actuators of the unmanned aerial vehicle, the data of control input to actuators of the unmanned aerial vehicle; and
a navigation system including:
a self-calibrating vehicle dynamic model component providing linear and rotational accelerations of the unmanned aerial vehicle utilizing control input and previously estimated velocity and a

Assignees

• Ecole Polytechnique Fed Lausanne Epfl

Inventors

• Khaghani Mehran
• Skaloud Jan

Classifications

• G01S19/42

  Determining position · CPC title

• G08G5/0069 Primary

  Physics · mapped topic

• G01C21/165

  combined with non-inertial navigation instruments · CPC title

• G05D1/101 Primary

  specially adapted for aircraft · CPC title

• G05D1/0088

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