Systems and methods for unmanned vehicles having self-calibrating sensors and actuators

US10990093B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-10990093-B2
Application numberUS-201816011760-A
CountryUS
Kind codeB2
Filing dateJun 19, 2018
Priority dateNov 7, 2014
Publication dateApr 27, 2021
Grant dateApr 27, 2021

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  5. First independent claim

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Abstract

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Systems and methods of unmanned vehicles having self-calibrating sensors and actuators are provided. The unmanned vehicle comprises a communication interface and a processor for controlling a propulsion system of the vehicle and receiving sensor data from one or more sensors of the vehicle. The processor is configured to operate in a guided calibration mode by controlling the propulsion system according to commands received from an external guided control system, while processing the sensor data to determine a degree of certainty on a calibration the sensor data and a position of the vehicle. The processor determines that the degree of certainty is above a threshold value associated with safe operation of the propulsion system in an autonomous calibration mode, and subsequently switch operation of the propulsion system to the autonomous calibration mode based on the determination that the degree of certainty is above the threshold value.

First claim

Opening claim text (preview).

What is claimed is: 1. An unmanned vehicle comprising: a chassis; a processor for controlling a propulsion system of the unmanned vehicle and receiving sensor data from one or more sensors of the unmanned vehicle, the processor configured to: enumerate one or more unmanned vehicle capabilities by querying one or more of the propulsion system and the one or more sensors of the unmanned vehicle; and operate the propulsion system in an autonomous calibration mode by: automatically controlling the propulsion system to move the chassis; collecting the sensor data from the one or more sensors; and processing the sensor data using one or more uncertainty propagation models to determine at least one degree of certainty on the calibration; determine that the degree of certainty is above a threshold value; and subsequently switch operation of the propulsion system to an operational mode based on the determination that the degree of certainty is above the threshold value. 2. The unmanned vehicle of claim 1 , wherein the processor is further configured to process the sensor data using one or more uncertainty propagation models to determine the degree of certainty of one or more of: a respective calibration of a relationship between uncertainty on sensor measurements with respect to the position of the chassis; a respective location of each of the one or more sensors with respect to the chassis; a respective orientation of each of the one or more sensors with respect to the chassis; and, one or more of respective shapes and respective location of sensed features. 3. The unmanned vehicle of claim 1 , wherein the one or more sensors comprise on or more of: cameras, LIDAR (Light Detection and Ranging) devices, laser sensing devices, radar devices, accelerometers, and magnetometers. 4. An unmanned vehicle comprising: a chassis; a communication interface; and a processor for controlling a propulsion system of the unmanned vehicle and receiving sensor data from one or more sensors of the unmanned vehicle, the processor configured to: enumerate one or more unmanned vehicle capabilities by querying one or more of the propulsion system and the one or more sensors of the unmanned vehicle; in a guided calibration mode, while controlling the propulsion system according to commands received via the communications interface from an external guided control system, process the sensor data to determine at least one degree of certainty on a calibration of one or more of the sensor data and a position of the chassis; determine that the degree of certainty is above a threshold value associated with a safe operation of the propulsion system in an autonomous calibration mode; and subsequently switch operation of the propulsion system to the autonomous calibration mode based on the determination that the degree of certainty is above the threshold value. 5. The unmanned vehicle of claim 4 , wherein enumerating the one or more unmanned vehicle capabilities one or more of: receiving a weight of the unmanned vehicle; receiving one or more dimensions of the unmanned vehicle; autodetecting each of the one or more sensors; receiving a list of the one or more sensors; and using a scanner to scan one or more graphical identifiers of the one or more sensors. 6. The unmanned vehicle of claim 4 , wherein the processor is further configured to determine that the one or more enumerated unmanned vehicle capabilities support a performance level threshold, and subsequently enable the guided calibration mode based on the determination that the one or more enumerated unmanned vehicle capabilities satisfies the performance level threshold. 7. The unmanned vehicle of claim 4 , wherein the processor is further configured to process the sensor data using one or more uncertainty propagation models to determine the degree of certainty of one or more of: a respective calibration of a relationship between uncertainty on sensor measurements with respect to the position of the chassis; a respective location of each of the one or more sensors with respect to the chassis; a respective orientation of each of the one or more sensors with respect to the chassis; and, one or more of respective shapes and respective location of sensed features. 8. The unmanned vehicle of claim 4 , wherein the one or more sensors comprise on or more of: cameras, LIDAR (Light Detection and Ranging) devices, laser sensing devices, radar devices, accelerometers, and magnetometers. 9. An unmanned vehicle comprising: a processor for controlling a propulsion system of the unmanned vehicle and receiving sensor data from one or more sensors of the unmanned vehicle, the processor configured to: operate the propulsion system in an operational mode; detect a sensor error; and subsequently switch operation of the propulsion system to an autorecovery mode based on the detected sensor error, wherein the autorecovery mode comprises enumerating one or more unmanned vehicle capabilities by querying one or more of the propulsion system and the one or more sensors of the unmanned vehicle. 10. The unmanned vehicle of claim 9 , wherein the autorecovery mode comprises using the propulsion system to stop movement of the unmanned vehicle. 11. The unmanned vehicle claim 9 , wherein the enumerating the one or more unmanned vehicle capabilities comprises one or more of: receiving sensor capability data; and autodetecting sensor capability data. 12. The unmanned vehicle of claim 9 , the processor further configured to: determine that an enumeration of the unmanned vehicle capabilities satisfies a performance level threshold based on the enumerating the one or more unmanned vehicle capabilities; and subsequently switch operation of the propulsion system to a guided calibration mode based on the determination that the enumeration of the unmanned vehicle capabilities satisfies the performance level threshold. 13. The unmanned vehicle of claim 9 , wherein the sensor error is based on one or more of: a boundary of an estimated parameter; and a rate of change of the estimated parameter. 14. The unmanned vehicle of claim 9 , wherein the one or more sensors comprise on or more of: cameras, LIDAR (Light Detection and Ranging) devices, laser sensing devices, radar devices, accelerometers, and magnetometers. 15. The unmanned vehicle of claim 1 , wherein the enumerating the one or more unmanned vehicle capabilities comprises one or more of: receiving a weight of the unmanned vehicle; receiving one or more dimensions of the unmanned vehicle; autodetecting each of the one or more sensors; receiving a list of the one or more sensors; and using a scanner to scan one or more graphical identifiers of the one or more sensors. 16. The unmanned vehicle of claim 1 , wherein the processor is further configured to determine that the one or more enumerated unmanned vehicle capabilities support a performance level threshold, and subsequently enable the autonomous calibration mode based on the determination that the one or more enumerated unmanned vehicle capabilities satisfies the performance level threshold. 17. The unmanned vehicle of claim 1 , wherein the enumerating the one or more unmanned vehicle capabilities comprises one or more of: receiving sensor capability data; and autodetecting sensor capability data. 18. The unmanned vehicle of claim 4 , wherein the enumerating the one or more unmanned vehicle capabilities comprises one or more of: receiving sensor capability data; and autodetecting sensor capability data. 19. The unmanned vehicle of claim 9

Assignees

Inventors

Classifications

  • using a video camera in combination with image processing means · CPC title

  • Physics · mapped topic

  • G05D1/024Primary

    in combination with a laser (lasers per se H01S) · CPC title

  • G05D1/0011Primary

    associated with a remote control arrangement · CPC title

  • from positioning sensors located off-board the vehicle, e.g. from cameras · CPC title

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What does patent US10990093B2 cover?
Systems and methods of unmanned vehicles having self-calibrating sensors and actuators are provided. The unmanned vehicle comprises a communication interface and a processor for controlling a propulsion system of the vehicle and receiving sensor data from one or more sensors of the vehicle. The processor is configured to operate in a guided calibration mode by controlling the propulsion system …
Who is the assignee on this patent?
Clearpath Robotics Inc
What technology area does this patent fall under?
Primary CPC classification G05D1/024. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Apr 27 2021 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 12 related publications on this page (citations in our corpus or others sharing the same primary CPC).