Control normalization for unmanned autonomous systems

• US 9,545,995 B1
• Filed: 07/14/2015
• Issued: 01/17/2017
• Est. Priority Date: 07/14/2015
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Chau, Kiet Tuan, Canoy, Michael-David Nakayoshi, DeVico, Michael Orlando, Sprigg, Stephen Alton
• Primary Examiner(s): Zanelli, Michael J
• Application Number:
  US14/798,715
• Publication Number:
  US 20170015405A1
• Time in Patent Office: 553 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 10/10 Rotorcrafts
• 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: G05B 13/04 involving the use of models or simulators
• CPC Class Codes: G05D 1/0022 characterised by the communication link data switching networks in general H04L12/00

Abstract

Methods, systems, and process-readable media include an autonomous vehicle override control system that receives override commands from a pilot qualified on a first type of unmanned autonomous vehicle (UAV) and translates the inputs into suitable commands transmitted to a target UAV of a second UAV type. A pilot'"'"'s certification for a first UAV type may be determined from the pilot'"'"'s login credentials. The system may obtain a first control model for the first UAV type and a second control model for the target UAV. Pilot input commands processed through the first control model may be used to calculate movements of a virtual UAV of the type. The system may estimate physical movement of the target UAV similar to the first physical movement, and generate an override command for the target UAV using the second control model and the second physical movement. Control models may accommodate current conditions and pilot experience.

Claims

1. A method for an autonomous vehicle override control system to provide override commands to a target unmanned autonomous vehicle (UAV), comprising:

identifying, via a processor of the autonomous vehicle override control system, a certification for a remote pilot for a first UAV type based on login credentials from the remote pilot;

obtaining, via the processor, a first control model for the first UAV type based on the certification;

obtaining, via the processor, a second control model for the target UAV of a second UAV type;

receiving, via the processor, an input command from a control input device corresponding to the first UAV type;

calculating, via the processor, a first physical movement of a virtual UAV of the first UAV type using the first control model and the input command;

estimating, via the processor, a second physical movement of the target UAV that is similar to the first physical movement; and

generating, via the processor, an override command for the target UAV using the second control model and the second physical movement.

2. The method of claim 1, further comprising transmitting, via the processor, the override command to the target UAV.

3. The method of claim 2, further comprising:

obtaining, via the processor, connection information for communicating with the target UAV, wherein the connection information is one or more of an access code, a transmission frequency, a transmission medium, an identifier of an intermediary receiver device, and a message format, and

wherein transmitting the override command to the target UAV comprises;

transmitting the override command to the target UAV using the connection information for the target UAV.

4. The method of claim 1, wherein identifying, via the processor of the autonomous vehicle override control system, the certification for the remote pilot for the first UAV type based on the login credentials from the remote pilot comprises:

obtaining, via the processor, a pilot profile for the remote pilot, wherein the pilot profile is a data record that includes data indicating one or more certifications for piloting different UAV types; and

identifying, via the processor, the certification for the first UAV type based on the pilot profile.

5. The method of claim 4, further comprising:

retrieving, via the processor, an experience profile based on the login credentials from the remote pilot, wherein the experience profile is stored within the pilot profile and includes data indicating experience with UAVs of the second UAV type; and

configuring, via the processor, the first control model and the second control model based at least in part on the experience profile.

6. The method of claim 5, wherein the experience with the UAVs of the second UAV type comprises a time spent controlling UAVs of the second UAV type, a diversity of maneuvers executed with regard to the UAVs of the second UAV type, or both.

7. The method of claim 5, further comprising updating, via the processor, the experience profile based on the input command.

8. The method of claim 1, wherein obtaining, via the processor, the first control model for the first UAV type based on the certification and obtaining, via the processor, the second control model for the target UAV of the second UAV type comprises retrieving, via the processor, the first control model and the second control model from a database of control models.

9. The method of claim 8, wherein retrieving, via the processor, the first control model and the second control model from the database of control models comprises downloading, via the processor, the database of control models from a remote server.

10. The method of claim 1, wherein calculating, via the processor, the first physical movement of the virtual UAV of the first UAV type using the first control model and the input command comprises:

performing, via the processor, a simulation using the first control model to determine how the virtual UAV of the first UAV type would move in response to receiving the input command.

11. The method of claim 10, wherein performing, via the processor, the simulation using the first control model to determine how the virtual UAV would move in response to receiving the input command comprises:

identifying, via the processor, a setting associated with the virtual UAV for an engine, a flap, an actuator, a rotor, a ballast, or any combination thereof.

12. The method of claim 10, wherein performing, via the processor, the simulation using the first control model to determine how the virtual UAV would move in response to receiving the input command comprises:

identifying, via the processor, a change in an altitude of the virtual UAV, a speed of the virtual UAV, a roll state of the virtual UAV, a pitch state of the virtual UAV, a yaw state of the virtual UAV, or any combination thereof.

13. The method of claim 1, wherein estimating, via the processor, the second physical movement that is similar to the first physical movement comprises:

identifying, via the processor, a first component of the target UAV that has a similar function as a second component of the virtual UAV.

14. The method of claim 1, wherein generating, via the processor, the override command for the target UAV using the second control model and the second physical movement comprises:

performing, via the processor, a reverse simulation using the second control model to identify the override command that would cause the target UAV to move according to the second physical movement.

15. The method of claim 1, further comprising:

obtaining, via the processor, information regarding current conditions at the target UAV; and

configuring, via the processor, the first control model and the second control model based at least in part on the information regarding the current conditions at the target UAV.

16. The method of claim 15, wherein the information regarding the current conditions at the target UAV includes sensor data from the target UAV, settings of instruments of the target UAV, weather conditions near the target UAV, or any combination thereof.

17. The method of claim 15, further comprising synchronizing, via the processor, a display, the control input device, or both to the information regarding the current conditions at the target UAV.

18. A computing device, comprising a processor configured with processor-executable instructions to:

identify a certification for a remote pilot for a first unmanned autonomous vehicle (UAV) type based on login credentials from the remote pilot;

obtain a first control model for the first UAV type based on the certification;

obtain a second control model for a target UAV of a second UAV type;

receive an input command from a control input device corresponding to the first UAV type;

calculate a first physical movement of a virtual UAV of the first UAV type using the first control model and the input command;

estimate a second physical movement of the target UAV that is similar to the first physical movement of the virtual UAV; and

generate an override command for the target UAV using the second control model and the second physical movement.

19. The computing device of claim 18, wherein the processor is further configured with processor-executable instructions to transmit the override command to the target UAV.

20. The computing device of claim 18, wherein the processor is further configured with processor-executable instructions to identify the certification for the remote pilot for the first UAV type based on the login credentials from the remote pilot by:

obtain a pilot profile for the remote pilot, wherein the pilot profile is a data record that includes data indicating one or more certifications for piloting different UAV types; and

identify the certification for the first UAV type based on data within the pilot profile.

21. The computing device of claim 20, wherein the processor is further configured with processor-executable instructions to:

retrieve an experience profile based on the login credentials from the remote pilot, wherein the experience profile is stored within the pilot profile and includes data indicating experience with UAVs of the second UAV type; and

configure the first control model and the second control model based at least in part on the experience profile.

22. The computing device of claim 21, wherein the processor is further configured with processor-executable instructions to update the experience profile based on the input command.

23. The computing device of claim 18, wherein the processor is further configured with processor-executable instructions to obtain the first control model for the first UAV type based on the certification and the second control model for the second UAV type by retrieving the first control model and the second control model from a database of control models.

24. The computing device of claim 23, wherein the processor is further configured with processor-executable instructions to retrieve the first control model and the second control model from the database of control models by downloading the database of control models from a remote server.

25. The computing device of claim 18, wherein the processor is further configured with processor-executable instructions to calculate the first physical movement of the virtual UAV using the first control model and the input command by performing a simulation using the first control model to determine how the virtual UAV would move in response to receiving the input command.

26. The computing device of claim 18, wherein the processor is further configured with processor-executable instructions to estimate the second physical movement of the target UAV that is similar to the first physical movement of the virtual UAV by identifying a first component of the target UAV that has a similar function as a second component of the virtual UAV.

27. The computing device of claim 18, wherein the processor is further configured with processor-executable instructions to generate the override command for the target UAV using the second control model and the second physical movement by performing a reverse simulation using the second control model to identify the override command that would cause the target UAV to move according to the second physical movement.

28. The computing device of claim 18, wherein the processor is further configured with processor-executable instructions to:

obtain information regarding current conditions at the target UAV; and

configure the first control model and the second control model based at least in part on the information regarding the current conditions at the target UAV.

29. A computing device, comprising:

means for identifying a certification for a remote pilot for a first unmanned autonomous vehicle (UAV) type based on login credentials from the remote pilot;

means for obtaining a first control model for the first UAV type based on the certification;

means for obtaining a second control model for a target UAV of a second UAV type;

means for receiving an input command from a control input device corresponding to the first UAV type;

means for calculating a first physical movement of a virtual UAV of the first UAV type using the first control model and the input command;

means for estimating a second physical movement of the target UAV that is similar to the first physical movement of the virtual UAV; and

means for generating an override command for the target UAV using the second control model and the second physical movement.

30. A non-transitory processor-readable storage medium having stored thereon processor-executable instructions configured to cause a processor of a computing device to perform operations comprising:

identifying a certification for a remote pilot for a first unmanned autonomous vehicle (UAV) type based on login credentials from the remote pilot;

obtaining a first control model for the first UAV type based on the certification;

obtaining a second control model for a target UAV of a second UAV type;

receiving an input command from a control input device corresponding to the first UAV type;

calculating a first physical movement of a virtual UAV of the first UAV type using the first control model and the input command;

estimating a second physical movement of the target UAV that is similar to the first physical movement of the virtual UAV; and

generating an override command for the target UAV using the second control model and the second physical movement.