KR102304662B1 - Navigation filtering for reproduction of accident of unmanned vehicle - Google Patents

Abstract

Provided is a navigation filtering method for reproducing an accident of an uncrewed vehicle (UV) which comprises a plurality of measuring units. The method comprises: a step of, when a disorder in the plurality of measuring units is detected, identifying a disorder status filter model corresponding to a navigation filter for the UV (the navigation filter generates a navigation solution from an input for a random given point of time, and the navigation solution includes one or more of the position, speed, and posture of the UV at the given point of time, and according to the corresponding disorder status filter model, regardless of the measurement data of a specific type provided by the detected measuring units, another type of measurement data provided by another of the plurality of measuring units is taken as an input, so the navigation solution is calculated in the reverse direction); and a step of calculating the navigation solution by using the corresponding disorder status filter model for a point of time which is subsequent to the disorder.

Description

Navigation filtering for the reproduction of accidents of unmanned vehicles

The present disclosure relates to navigation filtering for reproduction of an accident of an unmanned vehicle (UV).

With the development of autonomous driving technology, the number of cases in which an unmanned vehicle (UV) is applied in an industrial environment is increasing. For autonomous driving, UV can use a navigation system. The UV's navigation system bases current navigation information (which represents, for example, the UV's position, velocity, and attitude) based on previous navigation information and measurement information from inertial sensors such as gyroscopes or accelerometers. It can be based on the inertial navigation calculated by In inertial navigation, since the integration is repeated, the navigation error tends to accumulate more and more over time. These navigation errors may be mitigated or eliminated with the aid of an external navigation system, for example, a satellite navigation system such as a Global Navigation Satellite System (GNSS). For example, when a satellite navigation system is combined, UV's navigation system can use the satellite measurement data in a navigation algorithm that drives a filter such as an Extended Kalman Filter (EKF).

Many existing systems for reproducing accidents that occur while driving UV use an image black box that records image data. Such thought-reproduction methods are often accompanied by manual analysis, and there is a growing interest in reducing the time required for analysis and/or increasing the clarity of the analysis.

Navigation filtering for the reproduction of an accident of an unmanned vehicle (UV) is disclosed in this document.

In an example, a method of navigation filtering for reproduction of an accident of an unmanned vehicle (UV) including a plurality of measurement units includes: When it is detected that a failure occurs among the plurality of measurement units, Identifying the corresponding fault state filter model of the navigation filter for the UV (the navigation filter generates a navigation solution from the input for any given point in time, the navigation solution is the position, velocity of the UV at the given point in time) and attitude; and according to a corresponding fault state filter model, other types of measurement data provided by another of the plurality of measurement units, irrespective of the particular type of measurement data provided by the detected measurement units. is taken as input and the navigation solution is calculated in the reverse direction); and for a time point following the failure, calculating a navigation solution using the corresponding failure state filter model.

The previous summary is provided to introduce in a simplified form some aspects that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to delineate the scope of the claimed subject matter. Furthermore, claimed subject matter is not limited to implementations that provide any or all advantages discussed herein.

According to the present disclosure, navigation information about UV may be used to reproduce an accident that occurred in UV.

According to the present disclosure, in order to reproduce the accident of UV, it is possible to configure a navigation filter that provides a navigation solution representing the position, velocity and/or attitude of the UV in the reverse direction.

According to the present disclosure, when it is detected that a failure has occurred among several measuring units of UV, by processing measurement data provided by another of several measuring units of UV, and possibly also using a dynamic model of UV, the navigation solution can be calculated.

1 is a block diagram showing an example of a navigation and control system of an exemplary unmanned vehicle (UV).
FIG. 2 is a view for explaining various methods of calculating a navigation solution for UV of FIG. 1 .
FIG. 3 is a diagram for explaining exemplary navigation filtering for reproduction of the UV accident of FIG. 1 .
4 shows an exemplary decentralized filter for use in the navigation filtering of FIG. 3 .
5 is a flowchart showing an example of a process of navigation filtering for reproduction of the incident of UV of FIG. 1 ;

Various terms used in the present disclosure are selected from the terminology of common terms in consideration of their functions in this document, which may be differently recognized according to the intention of those skilled in the art, practice, or emergence of new technology. In certain instances, some terms may be given meanings as set forth in the Detailed Description. Accordingly, terms used in this document should be defined consistent with their meaning in the context of the present disclosure and not simply by their names.

In this document, the terms “comprise”, “have” and the like are used when specifying the presence of an element listed hereinafter, such as a certain feature, number, step, operation, component, information, or combination thereof. Unless otherwise indicated, these terms and variations thereof are not intended to exclude the presence or addition of other elements.

As used herein, the terms “first,” “second,” and the like are intended to identify several elements that resemble each other. Unless otherwise stated, such terms are not intended to impose limitations, such as the specific order of these elements or their use, but are merely used to refer to the various elements separately. For example, an element may be referenced in one example by the term "first" while the same element may be referenced in another example by a different ordinal number, such as "second" or "third." In such instances, these terms do not limit the scope of the present disclosure. Also, use of the term "and/or" in a list of multiple elements includes all possible combinations of those listed, including any one or multiple of those listed. Furthermore, expressions in the singular form include the meaning of the plural unless clearly used otherwise.

Certain examples of the present disclosure will now be described in detail with reference to the accompanying drawings. However, the present disclosure may be embodied in many different forms and should not be construed as being limited to the examples presented in this document. Rather, these examples are given to provide a better understanding of the scope of the present disclosure.

1 is a block diagram showing an example of an exemplary UV 10 navigation and control system 100 . Examples of UV 10 include mobile robots (eg, wheeled mobile robots), drones (eg, rotorcraft drones), other types of unmanned ground vehicles (UGVs), other types of Including Unmanned Aerial Vehicle (UAV), etc.

The exemplary navigation and control system 100 of FIG. 1 provides a control input that causes the UV 10 to have a controlled position, velocity and/or attitude, and a control input for the UV 10 and Auxiliary information from GNSS such as satellite navigation systems, especially Global Positioning Systems (GPS), along with a mechanism for calculating navigation information in a Dead Reckoning (DR) manner using a dynamic model of UV (10). It has a mechanism to receive and use it.

In the example of FIG. 1 , the navigation and control system 100 includes a plurality of measurement units 110 , an actuator 120 , a storage unit 130 and a processing unit 150 . include Other example implementations of the navigation and control system 100 are also contemplated. For example, the navigation and control system 100 may also include additional components not shown and/or may include some but not all of the components shown in FIG. 1 .

In the example shown, the plurality of measurement units 110 include an Inertial Measurement Unit (IMU) 112 (which includes a gyroscope and/or accelerometer), a geomagnetic sensor 114 (which is a magnetometer). ) and a satellite navigation receiver 116 , which may be referred to individually as measurement unit 100 or collectively as measurement unit 110 .

In the illustrated example, the gyroscope of the inertial measurement unit 112 outputs a gyro output signal carrying angular velocity measurement data. Then, the processing unit 150 calculates postures such as roll angle, pitch angle, and yaw angle (ie, azimuth) of the UV 10 based on the angular velocity measurement data received from the gyroscope. can be used to For example, the gyroscope may be a three-axis gyroscope.

In the illustrated example, the accelerometer of the inertial measurement unit 112 outputs an accelerometer output signal carrying acceleration measurement data. The processing unit 150 may then use the acceleration measurement data received from the accelerometer to calculate the roll angle and pitch angle of the UV 10 . For example, the accelerometer may be a three-axis accelerometer.

In the illustrated example, the geomagnetic sensor 114 outputs a magnetometer output signal carrying magnetic field measurement data. The processing unit 150 then calculates the azimuth of the UV 10 based on the magnetic field measurement data received from the geomagnetic sensor 114 and also based on the calculated roll angle and the calculated pitch angle of the UV 10 . can be calculated For example, the geomagnetic sensor may be a three-axis magnetometer.

In the example of FIG. 1 , the satellite navigation receiver 116 receives a satellite navigation signal from a navigation satellite. Then, the processing unit 150 processes the satellite navigation signal based on the received satellite navigation signal, for example, to obtain satellite measurement data (eg, pseudorange and/or pseudorange between the visible satellite and the satellite navigation receiver 116 ). Such satellite measurement data generated from a satellite navigation signal by the satellite navigation receiver 116 or by generating a pseudorange rate and/or latitude, longitude and/or azimuth of the satellite navigation receiver 116 is converted into a satellite navigation receiver. By receiving from 116 , the position, velocity and/or attitude of UV 10 may be determined. For example, the satellite navigation receiver 116 may be a GPS receiver.

In some example implementations, the plurality of measurement units 110 may further include additional sensors (eg, odometry and/or distance sensors) for navigation of the UVs 10 , such as Additional sensors may provide other measurement data (eg, speed measurement data and/or distance measurement data). The processing unit 150 may then use such measurement data to calculate the position, velocity and/or pose of the UV 10 .

In the example of FIG. 1 , under the control of the processing unit 150 , eg, in response to a control input applied from the processing unit 150 , the actuator 120 is activated by the UV 10 (or any component thereof, such as a wheel). actuation mechanism) is a controllable unit operative to position it in a predetermined position, move it at a predetermined speed and/or orient it in a predetermined direction. For example, the actuator 120 may include an electric motor actuator, a rotary actuator, and/or other types of actuators.

In the example of FIG. 1 , the storage unit 130 stores various information. For example, the storage unit 130 may include a computer readable storage medium that stores data in a non-transitory form. Therefore, the storage unit 130 may store various information therein, for example, a set of instructions to be executed by the processing unit 150 and/or other information.

In some example implementations, the storage unit 130 may store respective types of measurement data received from the plurality of measurement units 110 (eg, over a specific time period), which may include UV(10) 10 , as described below. ) can be retrieved and used for navigation filtering (in particular, reverse filtering, such as estimation of the position, velocity and/or attitude of the UV 10 at an earlier time point from a measurement at a later time point) .

In the example of FIG. 1 , the processing unit 150 controls the overall operation of the navigation system 100 . For example, processing unit 150 may be implemented as a processor or other processing circuitry to perform the operations described herein.

In the illustrated example, the processing unit 150 performs navigation filtering to reproduce the incident of the UV 10 . As such, the navigation and control system 100 of the UV 10 analyzes the accident by analyzing internal factors such as navigation information about the UV 10 in addition to or instead of external factors such as the scene or scene where the accident occurred. and make available for reproduction. This could be caused by an accident in UV 10 , for example failure of some measuring unit 110 of UV 10 (which provides measurement data), some controllable unit of UV 10 (which is controlled such as actuator 120 ). input) and/or the failure of other components of UV 10 is significant.

In such navigation filtering, as shown in FIG. 2 , the processing unit 150 may calculate a navigation solution for the UV 10 in various ways. In the example of FIG. 2 , the UV 10 initially starts to move from the departure point 210 and finally reaches the arrival point 220 , but suppose that an accident occurs at the point 215 on the way. Thereafter, the processing unit 150 can identify the particular time interval to be analyzed in the reproduction of the incident as the time interval spanning from the start time 230 to the end time 240 of such a movement, and within this time interval given For a point in time, one can calculate the navigation solution for UV 10 in the following manner: (i) as indicated by arrow 260 (eg, as with driving the navigation filter in real time) generate a navigation solution forward in time (ie, drive a “forward filter”); (ii) generating a navigation solution in a temporally backward direction (ie, driving a “reverse filter”), as indicated by arrow 270 ; or (iii) combining the forward generated navigation solution and the backward generated navigation solution, as indicated by arrow 280, to produce a refined navigation solution (i.e., consisting of a forward filter part and a reverse filter part). It uses a "double filter" structure).

In various examples, the processing unit 150 may perform navigation filtering as described below, so that if it is detected that a failure has occurred in the measurement unit 110 or the actuator 120 at the time of the accident 235, Among other things, for a time point subsequent to the incident point 235 , such a failed component may have as little impact as possible on finding a navigation solution (eg, by using a reverse filter).

Referring now to FIG. 3 , exemplary navigation filtering for reproducing the incident of UV 10 is described in greater detail.

In some example implementations, as represented by block 310 , processing unit 150 may initialize a navigation filter for UV 10 . The navigation filter may be configured to filter the input for any given point in time to provide a navigation solution.

In some example implementations, initialization of the navigation filter for UV 10 may include configuring the forward filter portion of the navigation filter as a forward filter model. The forward filter model is a filter model in which each type of measurement data provided from a plurality of measurement units 100 is taken as an input of a navigation filter to calculate a navigation solution, or measurement data provided from a specific one of the plurality of measurement units 100 is It may be another filter model that is not taken as input to the navigation filter. In a specific example, the forward filter may be configured to have a structure of a distributed filter (eg, a federated filter structure of a No-Reset (NR) mode). 4 shows a distributed filter 400 as an example of such a forward filter. The distributed filter 400 has an inertial navigation system (INS) 412 coupled therein. In this example, INS 412 is employed as a primary navigation system or reference system. INS 412 includes a filter that receives angular velocity and/or acceleration measurement data from IMU 112 and processes it to provide a navigation solution (eg, position, velocity, and/or attitude of UV 10 ). Also, in the example of FIG. 4 , the geomagnetic sensor 114 and the satellite navigation receiver 116 are used as other measurement units that provide other types of measurement data for correcting errors in the navigation solution of the INS 412 . Accordingly, the distributed filter 400 includes a local filter 414 for receiving magnetic field measurement data from the magnetometer 114 and a local filter 416 for receiving satellite measurement data from the satellite navigation receiver 116 . include more Each of the local filters 414 and 416 is provided with an INS navigation solution from the INS 412 as reference data. Each of the local filters 414 and 416 may be configured as a Kalman filter (eg, EKF). Further, in the example of FIG. 4 , the distributed filter 400 further includes a master filter 410 , which retrieves reference data from the INS 412 and local filters 414 and 416 respectively. Receive output data (eg, filtered state variables and covariances) from

In some example implementations, initialization of the navigation filter for UV 10 may include constructing a plurality of reverse filter models. As will be described in more detail below, the processing unit 150 may adjust the reverse filter portion of the navigation filter to operate according to the appropriate one of these filter models.

In some example implementations, as represented by block 320 , the processing unit 320 may detect whether any of the plurality of measurement units 110 have failed. Additionally, if there is a faulty measuring unit present, the processing unit 150 determines which of the plurality of measuring units 110 is such a faulty measuring unit 110 , and possibly when such a fault occurred. (i.e., the time of occurrence of a failure) can also be detected.

Accordingly, as also indicated by block 320 , processing unit 150 may determine the states of navigation and control system 100 in several (eg, one steady state case and several failure state cases, as shown). ) can be classified as In a specific example, the processing unit 150 may generate a navigation solution in a forward direction according to the forward filter model, and perform such failure detection based on the forward generated navigation solution. For example, as shown in FIG. 4 , a fault detector 424 is disposed between the local filter 414 and the master filter 410 , and the fault detector 426 is disposed between the local filter 416 and the master filter. 410 may be coupled. In this example, a propagator 420 may use the output of the master filter 410 to provide a reference signal for fault detection to the fault detectors 424 and 426, respectively, and the fault detectors 424 and 426, respectively. ) compares the outputs of the coupled local filters 414 and 416 with their respective reference signals to detect whether the corresponding measurement units 114 and 116 are faulty. Meanwhile, the INS 412 may separately detect whether the IMU 112 has failed (eg, by using a parity space technique).

In some example implementations, if it is determined that none of the measurement units 110 of the UV 10 have failed, as indicated by block 330 , the processing unit 150 sends the plurality of measurement units 110 to A predetermined reverse filter model (hereinafter referred to as a "steady state filter model") in which each type of measurement data provided by ) can be identified, eg, among a plurality of given reverse filter models. Then, for each of the plurality of time points within a specific time interval (which may be referred to as a “target time interval” hereinafter) for analysis in the reproduction of the incident of the UV 10 , the processing unit 150 generates a steady-state filter model According to this, the navigation solution can be calculated in the reverse direction.

In some example implementations, if it is determined that a failure has occurred in the satellite navigation receiver 116 of the plurality of measurement units 110 , as represented by block 340 , the processing unit 150 is configured to: Other inverse filter models (hereinafter referred to as "first failures") in which other types of measurement data provided by other of the plurality of measurement units 110 are taken as input, except for the satellite measurement data provided by 116 , and a navigation solution is calculated. may be referred to as "a state filter model" (eg, an Attitude and Heading Reference System (AHRS) filter model), eg, among a plurality of given inverse filter models. Then, for any given point within the target time interval and subsequent to the point of occurrence of the failure (which may hereinafter be referred to as a “post-failure time”), the processing unit 150 reverses according to the first failure state filter model. can be used to calculate the navigation solution. Optionally, for each of the remaining time points within the target time interval, the processing unit 150 calculates a navigation solution in the reverse direction (eg, according to a first faulty state filter model, according to a steady state filter model, or according to another filter model). can be calculated.

With respect to block 340 , estimating the position and velocity of the UV 10 at the post-failure time point following the failure of the satellite navigation receiver 116 with only the remaining measurement units 110 is more accurate than otherwise. It will be appreciated that there is a high probability that . Accordingly, in a specific example, the processing unit 150 calculates the posture of the UV 10 at such a point in the reverse direction as a navigation solution according to the first failure state filter model, and then converts the backward generated navigation solution to the satellite It can be used with other types of measurement data provided by a measurement unit 110 (eg, IMU 112 ) other than the navigation receiver 116 to calculate the position and/or velocity of the UV 10 at that point in time. have.

In some example implementations, if it is determined that a failure has occurred in the IMU 112 of the plurality of measurement units 110 , as represented by block 350 , the processing unit 150 is configured by the IMU 112 . Another reverse filter model in which other types of measurement data provided by the other of the plurality of measurement units 110 other than the provided measurement data (eg, angular velocity and/or acceleration measurement data) are taken as input and a navigation solution is calculated. (which may also be referred to as a “second failure state filter model” hereinafter) may be identified, for example, among a plurality of given reverse filter models. Then, for any post-failure time point within the target time interval, the processing unit 150 may calculate a navigation solution in the reverse direction according to the second failure state filter model. Optionally, for each of the remaining time points within the target time interval, the processing unit 150 calculates the navigation solution in the reverse direction (eg, according to the second faulty state filter model, according to the steady state filter model, or according to another filter model). can be calculated.

Additionally, according to the second fault condition filter model, a control input for the UV 10 can also be taken as an input. In general, the update rate of the satellite measurement data provided by the satellite navigation receiver 116 is usually in seconds (sec) with other measurement units 110 (eg, IMU 112 , geomagnetic sensor 114 ). etc.) (i.e., since the satellite navigation receiver 116 is a low speed measurement unit), if the control input for UV 10 is applied faster than such an update rate, the second fault condition filter model reflects this in the satellite measurement. Considering it with the data will help to obtain a more accurate navigation solution.

In some example implementations, if it is determined that a failure has occurred in the geomagnetic sensor 114 of the plurality of measurement units 110 , as represented by block 360 , the processing unit 150 may configure the geomagnetic sensor 114 . Another reverse filter model (hereinafter referred to as "third failure state" in which other types of measurement data provided by another of the plurality of measurement units 110 are taken as input, except for the magnetic field measurement data provided by filter model") may be identified, for example, among a plurality of given reverse filter models. Then, for any post-failure time point within the target time interval, the processing unit 150 may calculate a navigation solution in the reverse direction according to the third replacement filter model. Optionally, for each of the remaining time points within the target time interval, the processing unit 150 computes a navigation solution in the reverse direction (eg, according to a third fault state filter model, according to a steady state filter model, or according to another filter model). can be calculated.

Additionally, according to the third fault condition filter model, a control input for the UV 10 can also be taken as an input. Without the magnetic field measurement data received from the geomagnetic sensor 114 , obtaining a navigation solution based on the measurement data received from the IMU 112 often results in inaccurate results (eg, a significant error in the estimated azimuth of the UV 10 ). In view of leading to , such a filter model will be useful for calculating a more accurate navigation solution similar to the case of failure of the IMU 112 .

In some example implementations, the processing unit 150 detecting which one of the plurality of measurement units 100 has failed may cause the processing unit 150 to control the UVs 10 (eg, the navigation and control system 100 ). ) can be generalized to detecting whether a failure has occurred in another component. For example, at block 320 , processing unit 150 is further configured to operate according to a control input provided for UV 10 by a controllable unit of UV 10 , eg, processing unit 150 . It can be detected whether a failure has occurred in a controllable unit such as 120 . In this example, the steady state filter model identification at block 330 is conditioned on it being determined that no measurement unit 110 of UV 10 has failed as well as that no controllable unit of UV 10 has failed. It is also a condition that it is judged not to be. Further, if block 320 detects that a controllable unit (eg, actuator 120) of UV 10 has failed, processing unit 150 may, as represented by block 370: A predetermined reverse filter model (hereinafter referred to as "fourth failure state") in which each type of measurement data provided by the plurality of measurement units 110, except for the control input for the UV 10, is taken as input and a navigation solution is calculated. filter model") may be identified, for example, among a plurality of given reverse filter models. As an example, the fourth fault state filter model may be identical to the steady state filter model except that it does not take a control input for UV 10 as its input. Then, for any post-accident time point within the target time interval, the processing unit 150 may calculate a navigation solution in the reverse direction according to the fourth failure state filter model. Optionally, for each of the remaining time points within the target time interval, the processing unit 150 calculates the navigation solution in the reverse direction (eg, according to the fourth fault state filter model, according to the steady state filter model, or according to another filter model). can be calculated.

According to some example implementations, processing unit 150 calculates, for a point in time within a target time interval, a navigation solution generated in the reverse direction for the same point in time, according to the inverse filter model identified in any of blocks 330 - 370 . A refined navigation solution can be provided by performing backtracking in a way that is combined with the navigation solution generated in the forward direction.

According to some example implementations, processing unit 150 may provide the navigation solution calculated in any of the manners described above to an external computing device for processing (eg, for display).

5 is a flow diagram showing an exemplary process 500 of navigation filtering for the reproduction of an incident of UV 10 . For example, the process 500 may be performed by the navigation and control system 100 (particularly the processing unit 150 ) of the UV 10 . As another example, process 500 may be performed by a computing device external to UV 10 (eg, its processor). Other example flows of process 200 are also contemplated. For example, process 500 may also include additional operations not shown and/or may include some but not all of the operations illustrated in FIG. 5 .

In operation 510 , a respective type of measurement provided by a plurality of measurement units 110 of UV 10 for each of a plurality of time points within a specific time interval for analysis in a reproduction of an incident of UV 10 . Data is collected. For example, such measurement data may be stored in the storage unit 130 once received, and later retrieved from the storage unit 130 when it is recognized that an accident has occurred during the movement of the UV 10 . In a specific example, recognizing the occurrence of an incident of UV 10 involves identifying a specific time interval (eg, a time interval spanning from the start to the end by identifying the start and end points of such movement). can do.

In operation 520 , it is detected whether a failure has occurred among the plurality of measurement units 110 of the UV 10 within a specific time period. As described above, such detection may involve detecting which of the plurality of measurement units 110 has a failure, and possibly detecting when such a failure has occurred.

In operation 530 , if it is not detected that any of the plurality of measurement units 110 have failed, for each time point within the specified time interval, the navigation filter for the UV 10 (which at any given time point) A navigation solution is calculated using a steady-state filter model of (generating a navigation solution including at least one of the position, velocity, and attitude of the UV 10 at that point in time) from the input. According to the steady-state filter model, respective types of measurement data provided by the plurality of measurement units 110 are taken as filter inputs so that the navigation solution is reversed (ie, the filter input taken to calculate the navigation solution for each time point). is provided after that point in time).

In a particular example, for example, in an example in which it is further detected in act 520 whether any of the other components of UV 10 (eg, a controllable unit such as actuator 120 ) have failed, act 530 may include: Not only may it be conditional that none of the plurality of measurement units 110 is detected as having failed, but it may also be conditional that none of the other components of the UV 10 are detected as having failed. For details regarding this example, reference is made to the foregoing description, which is not discussed herein.

In operation 540 , when it is detected that a failure has occurred among the plurality of measurement units 110 , for at least a post-failure time point within a specific time interval, the corresponding failure state filter model of the navigation filter for UV 10 is used. Thus, the navigation solution is calculated. According to such a fault condition filter model, by the other of the plurality of measurement units 110 (which may also be referred to as a “normal measurement unit”) irrespective of the specific type of measurement data provided by the detected measurement unit. Another type of measurement data provided is taken as a filter input so that a navigation solution is calculated in the reverse direction (ie, for each point in time the filter input taken to calculate the navigation solution was provided after that point in time). For example, this fault condition filter model may be identified from among a plurality of predefined fault condition filter models (eg, the first through fourth fault condition filter models described above).

In a particular example, the detected failed measurement unit may be the satellite navigation receiver unit 116 , and/or the normal measurement unit may be the IMU 112 . In this example, the navigation solution calculated in operation 540 includes some of the position, velocity, and attitude of the UV 10 at the time point after the failure, and among the position, velocity, and attitude of the UV 10 at that time point. Others may be calculated based on such navigation solutions and other types of measurement data provided by normal measurement units.

In a particular example, the detected failed measurement unit may be the IMU 112 or geomagnetic sensor 114, and/or the normal measurement unit may be a satellite navigation receiver 116 that provides measurement data with a lower update rate than the failed measurement unit. . In this example, the control input for the UV 10 is also taken as an input according to the fault state filter model, so that the navigation solution can be calculated.

In a particular example, the calculated navigation solution, either in operation 530 or in operation 540 may be provided (eg, to a processor of an external computing device) for processing (eg, for display).

The following are various examples related to navigation filtering to reproduce the accident of UV.

In Example 1, the navigation filtering method for reproducing the accident of an unmanned vehicle (UV) including a plurality of measurement units is a navigation method for the above UV when a failure occurs among the plurality of measurement units. identifying a corresponding one of a plurality of failure state filter models of the filter (the navigation filter generates a navigation solution from the input for any given time point, the navigation solution includes the position, velocity and a different type of measurement data provided by the other one of the plurality of measurement units, irrespective of the specific type of measurement data provided by the detected measurement unit, according to the corresponding fault state filter model. measurement data is taken as the input and the navigation solution is calculated in the reverse direction), and for a time point subsequent to the failure, calculating the navigation solution using the corresponding fault state filter model.

Example 2 includes the subject matter of Example 1, wherein the method further includes detecting when the fault occurs in the detected measuring unit.

Example 3 includes the subject matter of Examples 1 or 2, wherein the method comprises, for a time point above, using a steady-state filter model, provided that none of the plurality of measurement units is detected to have failed. The method further comprises calculating a navigation solution, wherein, according to the steady-state filter model, respective types of measurement data provided by the plurality of measurement units are taken as the input and the navigation solution is calculated in the reverse direction.

Example 4 includes the subject matter of Example 3, wherein, for the above time point, calculating the navigation solution using the above steady-state filter model operates according to the control input for the above UV and any control contained in the above UV It is also conditional that the enabled unit is not detected as having failed.

Example 5 includes the subject matter of any of Examples 1-4, wherein the method comprises, for the time point, to calculate the navigation solution using the corresponding failure state filter model, the time point comprising: The method further includes collecting, for each of a plurality of time points within a specific time interval, respective types of measurement data provided by the plurality of measurement units.

Example 6 includes the subject matter of Example 5, wherein the method identifies the specific time interval as a time interval spanning from the start time to the end time by identifying a start time of movement of the UV and an end time of the movement of the UV. further comprising the step of

Example 7 includes the subject matter of any of Examples 1-6, wherein the method further comprises providing the calculated navigation solution for display.

Example 8 includes the subject matter of any of Examples 1-7, wherein the navigation solution comprises some of the position, velocity, and posture of the UV at the time point, the position, velocity, and Another part of the posture is calculated based on the navigation solution above and other types of measurement data above.

Example 9 includes the subject matter of Example 8, wherein the detected measurement unit is a satellite navigation receiver unit and/or the other measurement unit is an Inertial Measurement Unit (IMU).

Example 10 includes the subject matter of any of Examples 1-9, wherein the control input for the UV is also taken as an input according to the corresponding fault state filter model above to yield the navigation solution.

Example 11 includes the subject matter of Example 10, wherein the other types of measurement data have a lower update rate than the specific types of measurement data.

Example 12 includes the subject matter of Examples 10 or 11, wherein the detected measurement unit is an Inertial Measurement Unit (IMU) or a geomagnetic sensor unit and/or the other measurement unit is a satellite navigation receiver unit.

Example 13 includes the subject matter of any of Examples 1-12, wherein the unmanned vehicle is an Unmanned Ground Vehicle (UGV).

Example 14 includes the subject matter of any of Examples 1-12, wherein the unmanned vehicle is an Unmanned Aerial Vehicle (UAV).

Example 15 includes the subject matter of any of Examples 1-14, wherein the unmanned vehicle is a mobile robot.

In Example 16, a computing device includes a processor and a memory, wherein the memory is executable by the processor for navigation filtering for reproduction of an accident of an unmanned vehicle (UV) comprising a plurality of measurement units. Encoded as a set of computer program instructions, the set comprising instructions for identifying a corresponding one of a plurality of failure state filter models of a navigation filter for the UV when a failure has been detected among the plurality of measurement units (the navigation The filter generates a navigation solution from the input for any given time point, the navigation solution including at least one of the position, velocity and attitude of the UV at the given time point, and according to the corresponding fault state filter model above, Irrespective of the specific type of measurement data provided by the detected measurement unit, other types of measurement data provided by another one of the plurality of measurement units are taken as the input so that the navigation solution is calculated in the reverse direction; for a time point subsequent to the above fault, including an instruction for calculating the above navigation solution using the above corresponding fault state filter model.

Example 17 includes the subject matter of Example 16, wherein the set further includes instructions to detect when the failure occurs in the detected measurement unit.

Example 18 includes the subject matter of Examples 16 or 17, wherein the set comprises, for a time point above, using a steady-state filter model, provided that none of the plurality of measurement units is detected to have failed. Further comprising an instruction for calculating a navigation solution, wherein, according to the steady-state filter model, respective types of measurement data provided by the plurality of measurement units are taken as the input and the navigation solution is calculated in the reverse direction.

Example 19 includes the subject matter of Example 18, wherein, for the time point above, the instructions for calculating the navigation solution using the steady-state filter model above operate according to the control input for the UV above and any control contained in the UV above. It is also conditional that the enabled unit is not detected as having failed.

Example 20 includes the subject matter of any of Examples 16-19, wherein the set comprises, for the time point, to calculate the navigation solution using the corresponding fault state filter model, the time point comprising: and, for each of a plurality of time points within a specific time period, collecting respective types of measurement data provided by the plurality of measurement units.

Example 21 includes the subject matter of Example 20, wherein the set identifies the specific time interval as a time interval spanning from the start time to the end time by identifying a start time of movement of the UV and an end time of the movement of the UV. It further includes a command to

Example 22 includes the subject matter of any of Examples 16-21, wherein the set further includes instructions to provide the calculated navigation solution for display.

Example 23 includes the subject matter of any of Examples 16-22, wherein the navigation solution comprises some of the position, velocity and pose of the UV at the time point, the position, velocity, and Another part of the posture is calculated based on the navigation solution above and other types of measurement data above.

Example 24 includes the subject matter of Example 23, wherein the detected measurement unit is a satellite navigation receiver unit and/or the other measurement unit is an Inertial Measurement Unit (IMU).

Example 25 includes the subject matter of any of Examples 16-24, wherein the control input for the UV is also taken as an input according to the corresponding fault state filter model to yield the navigation solution.

Example 26 includes the subject matter of Example 25, wherein the other types of measurement data have a lower update rate than the specific types of measurement data.

Example 27 includes the subject matter of Examples 25 or 26, wherein the detected measurement unit is an Inertial Measurement Unit (IMU) or a geomagnetic sensor unit and/or the other measurement unit is a satellite navigation receiver unit.

Example 28 includes the subject matter of any of Examples 16-27, wherein the UV is an Unmanned Ground Vehicle (UGV).

Example 29 includes the subject matter of any of Examples 16-27, wherein the UV is an Unmanned Aerial Vehicle (UAV).

Example 30 includes the subject matter of any of Examples 16-29, wherein the UV is a mobile robot.

In Example 31, there is provided a computer-readable storage medium having stored thereon computer-executable instructions that, when executed by a computer processor, cause the computer processor to perform the method of any one of Examples 1-15.

In Example 32, an unmanned vehicle is provided that includes a computing device and a plurality of measurement units described in any of Examples 16-30.

In certain instances, any suitable type of apparatus, device, system, machine, etc. referred to herein may be, include, or be embodied in a computing device. A computing device may include a processor and a computer-readable storage medium readable by the processor. The processor may execute one or more instructions stored in a computer-readable storage medium. The processor may also read other information stored within the computer readable storage medium. Additionally, the processor may store new information in the computer-readable storage medium and update any information stored in the computer-readable storage medium. The processor is, for example, a central processing unit (CPU), a digital signal processor (DSP), a graphics processing unit (GPU), a processor core, a microprocessor. , a microcontroller, a Field-Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), other hardware and logic circuitry, or any suitable combination thereof. can A computer-readable storage medium is encoded with various information, such as a set of processor executable instructions and/or other information that can be executed by a processor. For example, a computer-readable storage medium may include computer program instructions that, when executed by a processor, cause a computing device (eg, a processor) to perform some operations disclosed herein and/or information, data, and/or information used in those operations; Variables, constants, data structures, etc. can be stored inside. Computer-readable storage media include, for example, read-only memory (ROM), random-access memory (RAM), volatile memory, non-volatile memory, removable Removable memory, non-removable memory, flash memory, solid-state memory, other types of memory devices, magnetic media such as hard disks, floppy disks and magnetic tapes, CDs - optical recording media such as ROM, DVD, magneto-optical media such as floppy disks, other types of storage devices and storage media, or any suitable combination thereof.

In certain instances, the acts, techniques, processes, or any aspect or portion thereof described herein may be embodied in a computer program product. Such computer programs may be implemented in any type (eg, compiled or interpreted) programming language that can be executed by a computer, such as assembly, machine language, procedural. It may be implemented in a language, an object-oriented language, etc., and may be combined with a hardware implementation. The computer program product may be distributed in the form of a computer-readable storage medium or may be distributed online. For online distribution, some or all of the computer program product may be temporarily stored or temporarily created in a server (eg, a computer-readable storage medium of the server).

The foregoing description has been presented to illustrate and describe some examples in detail. It will be appreciated by those skilled in the art that many modifications and variations are possible in light of the above teachings without departing from the scope of the present disclosure. In various instances, the above-described techniques are performed in a different order, and/or some of the components of the above-described systems, architectures, devices, circuits and the like are combined or combined in different ways, replaced by other components or equivalents thereof, or Appropriate results can be achieved even if substituted.

Therefore, the scope of the present disclosure should not be limited to the form disclosed, but should be defined by the following claims and their equivalents.

10: unmanned vehicle
100: navigation and control system
110: measuring unit
112: inertial measurement unit
114: geomagnetic sensor
116: satellite navigation receiver
120: actuator
130: storage unit
150: processing unit

Claims (16)

As a method of navigation filtering for reproduction of an accident of an unmanned vehicle (UV) including a plurality of measurement units,
when a specific one of the plurality of measurement units is detected, identifying a corresponding one of a plurality of failure state filter models of the navigation filter for UV, the specific measurement unit having a failure among the plurality of measurement units, the The navigation filter generates a navigation solution from an input for any given point in time, the navigation solution comprising at least one of a position, velocity and attitude of the UV at the given point in time, according to the corresponding fault state filter model: , that a specific type of measurement data provided from the specific measurement unit is not taken as the input, and other types of measurement data provided by another one of the plurality of measurement units are taken as the input so that the navigation solution is calculated in the reverse direction; Wow,
for a post-failure time point following the failure, calculating the navigation solution using the corresponding failure state filter model.
Way. According to claim 1,
The navigation solution includes some of the position, velocity and attitude of the UV at the time point after the failure, and another part of the position, velocity and attitude of the UV at the time point after the failure is the navigation solution and the other type calculated based on the measurement data,
Way. 3. The method of claim 2,
The other measurement unit is an Inertial Measurement Unit (IMU),
Way. According to claim 1,
a control input for the UV is also taken as an input according to the corresponding fault condition filter model to yield the navigation solution;
Way. 5. The method of claim 4,
The other type of measurement data has a lower update rate than the specific type of measurement data,
Way. 5. The method of claim 4,
wherein the other measuring unit is a satellite navigation receiver unit;
Way. According to claim 1,
calculating, for the given time point, the navigation solution using a steady-state filter model, provided that none of the plurality of measurement units is detected as having failed; according to which respective types of measurement data provided by the plurality of measurement units are taken as the input and the navigation solution is calculated in the reverse direction,
Way. A computer-readable storage medium having stored thereon computer-executable instructions that, when executed by a computer processor, cause the computer processor to perform the method according to any one of claims 1 to 7. A computing device comprising:
processor and
a memory encoded as a set of computer program instructions executable by the processor for navigation filtering for reproduction of an accident of an unmanned vehicle (UV) comprising a plurality of measurement units, the set comprising: Is,
instructions for identifying a corresponding one of a plurality of fault state filter models of the navigation filter for UV, when a specific one of the plurality of measurement units is detected, the specific measurement unit having a failure among the plurality of measurement units; The navigation filter generates a navigation solution from an input for any given point in time, the navigation solution comprising at least one of a position, velocity and attitude of the UV at the given point in time, according to the corresponding fault state filter model: , that a specific type of measurement data provided from the specific measurement unit is not taken as the input, and other types of measurement data provided by another one of the plurality of measurement units are taken as the input so that the navigation solution is calculated in the reverse direction; Wow,
for a post-failure time point following the failure, including instructions for calculating the navigation solution using the corresponding failure state filter model
computing device. 10. The method of claim 9,
The navigation solution includes some of the position, velocity and attitude of the UV at the time point after the failure, and another part of the position, velocity and attitude of the UV at the time point after the failure is the navigation solution and the other type calculated based on the measurement data,
computing device. 11. The method of claim 10,
The other measurement unit is an Inertial Measurement Unit (IMU),
computing device. 10. The method of claim 9,
a control input for the UV is also taken as an input according to the corresponding fault condition filter model to yield the navigation solution;
computing device. 13. The method of claim 12,
The other type of measurement data has a lower update rate than the specific type of measurement data,
computing device. 13. The method of claim 12,
wherein the other measuring unit is a satellite navigation receiver unit;
computing device. 10. The method of claim 9,
The set further includes instructions for calculating the navigation solution using a steady-state filter model for the given time point, provided that none of the plurality of measurement units is detected as having failed, According to a state filter model, respective types of measurement data provided by the plurality of measurement units are taken as the input and the navigation solution is calculated in the reverse direction;
computing device. An unmanned vehicle (UV) comprising a plurality of measurement units and a computing device according to any one of claims 9 to 15.

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