Unmanned aerial vehicle recovery system

• US 10,059,459 B2
• Filed: 05/28/2015
• Issued: 08/28/2018
• Est. Priority Date: 05/28/2015
• Status: Active Grant

• Current Assignee: Firmatek Software LLC
• Original Assignee: Kespry, Inc.
• Inventors: Clark, Robert Parker
• Primary Examiner(s): Cass, Jean Paul
• Application Number:
  US14/723,897
• Publication Number:
  US 20160347462A1
• Time in Patent Office: 1,188 Days
• Field of Search: 701 7
• CPC Class Codes: B64C 39/024 of the remote controlled vehicle type, i.e. RPV
• CPC Class Codes: B64D 17/62 Deployment
• CPC Class Codes: B64D 17/80 in association with aircraft, e.g. for braking thereof
• CPC Class Codes: B64D 43/02 for indicating aircraft speed or stalling conditions
• CPC Class Codes: B64U 10/13 Flying platforms
• CPC Class Codes: B64U 50/19 using electrically powered motors
• CPC Class Codes: B64U 70/83 using parachutes, balloons or the like
• CPC Class Codes: G05D 1/0072 to counteract a motor failure
• CPC Class Codes: G05D 1/0077 using redundant signals or controls
• 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 1/105 specially adapted for unpowered flight, e.g. glider, parachuting, forced landing parachutes per se B64D17/00

Abstract

An unmanned aerial vehicle includes a closely integrated emergency recovery and operation systems for an unmanned aerial vehicle with built-in levels of redundancy and independence to maximize the likelihood of a controlled velocity landing. The unmanned aerial vehicle may include multiple processors and multiple state estimating modules such as inertial measurement units to independently determine the operational and error status of the unmanned aerial vehicle. Base on predictive or projected computations, the emergency recovery system may determine a suitable time for a recovery action, such as parachute deployment, and execute the recovery action.

Claims

1. An unmanned aerial vehicle comprising:

a primary operation system in communication with a primary state estimator, the primary operation system being configured to operate the unmanned aerial vehicle based in part on the primary state estimator; and

a flight failure recovery system in communication with the primary operation system and a recovery state estimator different from the primary state estimator, the flight failure recovery system being configured to determine a suitable time to generate a deploy signal based at least in part on one or more signals from the recovery state estimator and one or more signals sent to the flight failure recovery system from the primary operation system during a time period following a determination of flight failure, and wherein the suitable time is determined by a predictive analysis provided by the flight failure recovery system that determines one or more predictive analysis optimal deployment times, the one or more predictive analysis optimal deployment times reducing parachute entanglement and parachute complications that cause an unsuccessful parachute landing.

2. The unmanned aerial vehicle of claim 1, wherein the flight failure recovery system comprises a parachute.

3. The unmanned aerial vehicle of claim 1, wherein the primary operation system is further configured to generate a recovery command signal indicating error in the primary operation system, and the flight failure recovery system is configured to receive the recovery command signal from the primary operation system.

4. The unmanned aerial vehicle of claim 1, wherein the flight failure recovery system is further configured to:

determine primary operation status indicating reliability of the primary operation system based in part on one or more signals from the recovery state estimator; and

generate the deploy signal further based at least in part on the primary operation status.

5. The unmanned aerial vehicle of claim 4, wherein the primary operation status indicates the primary operation system is reliable and the flight failure recovery system is configured to generate the deployment signal further based on the error signal from the primary operation system.

6. The unmanned aerial vehicle of claim 1, wherein each of the primary state estimator and the recovery state estimator comprises an inertial measurement unit (IMU).

7. The unmanned aerial vehicle of claim 3, wherein the suitable time to generate the deploy signal is based on at least one of:

the altitude of the unmanned aerial vehicle approximately when the flight failure recovery system receives the recovery command signal;

the velocity of the unmanned aerial vehicle approximately when the flight failure recovery system receives the recovery command signal;

the attitude of the unmanned aerial vehicle approximately when the flight failure recovery system receives the recovery command signal; and

one or more signals from the recovery state estimator after the flight failure recovery system receives the recovery command signal.

8. The unmanned aerial vehicle of claim 7, wherein the suitable time is based on the attitude of the aerial vehicle system determined from a gyroscope signal from the recovery state estimator using a sensor fusion filter.

9. The unmanned aerial vehicle of claim 7, wherein the flight failure recovery system is further configured to determine whether to generate the deployment signal at the suitable time.

10. The unmanned aerial vehicle of claim 1, wherein the flight failure recovery system is further configured to send one or more signals to the primary operation system to control at least part of the primary operation system.

11. A method for recovering an unmanned aerial vehicle comprising:

operating the unmanned aerial vehicle based at least in part on a primary operation system containing at least a primary state estimator;

determining that flight failure has occurred; and

determining a suitable time to generate a deploy signal based at least in part on one or more signals from a flight failure recovery state estimator different from the primary state estimator, and one or more signals from the primary operation system following the determination of flight failure, wherein the suitable time is determined by a predictive analysis provided by the flight failure recovery system that determines one or more predictive analysis optimal deployment times, the one or more predictive analysis optimal deployment times reducing parachute entanglement and parachute complications that cause an unsuccessful parachute landing.

12. The method of claim 11 further comprising generating a recovery command signal indicating error in a primary operation system of the unmanned aerial vehicle.

13. The method of claim 12 further comprising:

determining primary operation status indicating reliability of the recovery command signal based in part on one or more signals from the flight failure recovery state estimator; and

generating the deployment signal further based at least in part on the primary operation status.

14. The method of claim 13, further comprising generating the deployment signal further based on the recovery command signal, wherein the primary operation status indicates the recovery command signal is reliable.

15. The method of claim 11, wherein each of the primary state estimator and the recovery state estimator comprises an inertial measurement unit (IMU).

16. The method of claim 12, wherein the suitable time to generate the deploy signal is based on at least one of:

the altitude of the unmanned aerial vehicle approximately when the recovery module receives the recovery command signal;

the velocity of the unmanned aerial vehicle approximately when the recovery module receives the recovery command signal;

the attitude of the unmanned aerial vehicle approximately when the recovery module receives the recovery command signal; and

one or more signals from the recovery state estimator after receiving the recovery command signal.

17. The method of claim 16, wherein the suitable time is based on the attitude of the aerial vehicle system determined from a gyroscope signal from the recovery state estimator using a sensor fusion filter.

18. The method of claim 16 further comprising determining whether to generate the deployment signal at the suitable time.

19. The method of claim 11 further comprising generating one or more recovery control signals to control at least part of the unmanned aerial vehicle.

20. An intelligent emergency parachute deployment system for an unmanned aerial vehicle, the system comprising:

a parachute deployment system;

a dedicated inertial measurement unit (IMU) comprising a gyroscope and an accelerometer; and

a processor coupled to the dedicated IMU, the parachute deployment system, and a primary operation system for the unmanned aerial vehicle;

wherein, after a determination of flight failure, the processor is configured to monitor signals from the dedicated IMU to determine when to deploy the parachute based on altitude, velocity, and attitude of the unmanned aerial vehicle to enhance the chance of successful deployment of the parachute, and wherein the processor is configured to determine the suitable time by a predictive analysis provided by the flight failure recovery system that determines one or more predictive analysis optimal deployment times, the one or more predictive analysis optimal deployment times reducing parachute entanglement and parachute complications that cause an unsuccessful parachute landing.

21. A method for flight failure recovery of an unmanned aerial vehicle comprising:

operating the unmanned aerial vehicle with a first processor based in part on signals received by the first processor from a primary state estimator;

determining by the first processor that flight failure has occurred; and

after determining that flight failure has occurred, determining a suitable time to generate a flight failure recovery signal with a second processor based at least in part on one or more signals from a flight failure recovery state estimator different from the primary state estimator and one or more signals sent to the second processor from the first processor, wherein the suitable time is determined by a predictive analysis provided by the flight failure recovery system that determines one or more predictive analysis optimal deployment times, the one or more predictive analysis optimal deployment times reducing parachute entanglement and parachute complications that cause an unsuccessful parachute landing;

wherein the primary state estimator comprises a primary inertial measurement unit (IMU), the primary IMU comprising one or more gyroscopes, accelerometers, magnetometers, and/or barometers;

wherein the recovery state estimator comprises a recovery inertial measurement unit (IMU), the recovery IMU comprising one or more gyroscopes, accelerometers, magnetometers, and/or barometers; and

wherein the first processor, second processor, primary state estimator, and recovery state estimator reside on the unmanned aerial vehicle.

22. The method of claim 21, wherein the flight failure recovery signal initiates a parachute deployment.

23. The method of claim 21 further comprising determining whether at least part of the unmanned aerial vehicle is operational.

24. The method of claim 23, wherein the flight failure recovery signal initiates a controlled vertical descent.