CN111323043B - Sensor data processing method and system - Google Patents
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- CN111323043B CN111323043B CN202010225606.0A CN202010225606A CN111323043B CN 111323043 B CN111323043 B CN 111323043B CN 202010225606 A CN202010225606 A CN 202010225606A CN 111323043 B CN111323043 B CN 111323043B
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Abstract
The invention discloses a sensor data processing method and a sensor data processing system. The method comprises the steps of obtaining an acceleration value of an acceleration sensor, obtaining a geodetic coordinate acceleration value by converting the acceleration value into a geodetic coordinate system through position observation values of the sensor in an absolute coordinate system, a local coordinate system and a relative coordinate system, predicting the lower position observation values and system speed of the three coordinate systems by using the geodetic coordinate acceleration value to obtain corresponding position prediction values and system speed prediction values in the three coordinate systems, and correcting the system speed prediction values and the position observation values according to the system speed observation values by using complementary filtering. By means of navigation fusion of the sensor values in three different coordinate systems, the upper-layer control logic can acquire more accurate low-delay sensor fusion values in different coordinate systems, control accuracy is improved, and response time is shortened.
Description
Technical Field
The invention relates to the technical field of control, in particular to a sensor data processing method and system.
Background
The unmanned aerial vehicle is an aircraft mainly moving in the low-altitude field, and is widely applied to various industries. There are many different types of sensors on the drone for implementing different functions, and the data measured by the sensors are usually referenced by different types of coordinate systems, including: absolute coordinate system, local coordinate system, relative coordinate system, etc. The absolute coordinate system generally refers to a three-dimensional space coordinate system of a certain point fixed on the ground, for example, the navigation value of the aircraft GPS refers to the ground coordinate system, and the barometer refers to the sea level height; the relative coordinate system generally refers to a relative position relationship between two components, for example, a navigation value of an optical flow velocimeter is referred to a geodetic coordinate system, and an ultrasonic wave and laser infrared distance meters are referred to heights relative to the ground, etc.; the local coordinate system generally refers to a coordinate system using a local small range as a reference, for example, a two-dimensional code carpet in the UWB networking acquires a navigation value, a height and the like within a networking range.
However, in the related art, usually, only the sensor value in a certain coordinate system can be obtained at the same time for navigation, and the upper layer flight control logic cannot simultaneously obtain data in different coordinate systems for reference, which makes it difficult to perform accurate low-delay navigation.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides a sensor data processing method which can improve the numerical precision by fusing numerical values of a plurality of coordinate systems.
In a first aspect, an embodiment of the present invention provides: a sensor data processing method, comprising:
acquiring an acceleration value of an acceleration sensor and position observation values of the sensor in an absolute coordinate system, a local coordinate system and a relative coordinate system;
converting the acceleration value into a geodetic coordinate system to obtain a geodetic coordinate acceleration value;
predicting the position observation value and the system speed under the three coordinate systems by using the geodetic coordinate acceleration value to obtain corresponding position predicted values and system speed predicted values under the three coordinate systems;
and correcting the system speed predicted value and the position observed value according to the system speed observed value by utilizing complementary filtering.
Further, the converting the acceleration value into a geodetic coordinate system to obtain a geodetic coordinate acceleration value includes:
obtaining a coordinate acceleration value of the machine body under a coordinate system of the machine body according to the acceleration value and the acceleration deviation value;
and obtaining the geodetic coordinate acceleration value according to the machine coordinate acceleration value by utilizing the attitude rotation matrix.
And further, predicting the position observed value and the system speed under the three coordinate systems by using the geodetic coordinate acceleration value according to the sampling time interval of the acceleration sensor to obtain corresponding position predicted values and system speed predicted values under the three coordinate systems.
And further, acquiring a speed observation value and a noise observation value of the sensor in an absolute coordinate system, a local coordinate system and a relative coordinate system, and selecting the speed observation value of the coordinate system corresponding to the minimum noise observation value as a system speed observation value.
Further, the method also comprises the step of correcting the acceleration deviation value according to the system speed observation value by utilizing complementary filtering.
In a second aspect, an embodiment of the present invention provides: a sensor data processing system, comprising:
an acquisition unit: the system comprises a sensor, a local coordinate system and a relative coordinate system, wherein the sensor is used for acquiring an acceleration value of the acceleration sensor and position observation values of the sensor in the absolute coordinate system, the local coordinate system and the relative coordinate system;
an acceleration value conversion unit: the acceleration value is converted into a geodetic coordinate system to obtain a geodetic coordinate acceleration value;
a prediction unit: the geodetic coordinate acceleration value is used for predicting the position observation value and the system speed under the three coordinate systems to obtain corresponding position predicted values and system speed predicted values under the three coordinate systems;
a correction unit: and the device is used for correcting the predicted value of the system speed and the position observation value by utilizing complementary filtering according to the system speed observation value.
In a third aspect, an embodiment of the present invention provides: a sensor data processing apparatus comprising:
at least one processor, and a memory communicatively coupled to the at least one processor;
wherein the processor is adapted to perform the method of any of the first aspects by invoking a computer program stored in the memory.
In a fourth aspect, an embodiment of the invention provides: a computer-readable storage medium having stored thereon computer-executable instructions for causing a computer to perform the method of any one of the first aspects.
The embodiment of the invention has the beneficial effects that:
according to the embodiment of the invention, the acceleration value of the acceleration sensor and the position observation values of the sensor under an absolute coordinate system, a local coordinate system and a relative coordinate system are obtained, the acceleration value is converted into a geodetic coordinate system to obtain the geodetic coordinate acceleration value, the geodetic coordinate acceleration value is used for predicting the position observation values and the system speed under the three coordinate systems to obtain the corresponding position prediction values and the system speed prediction values under the three coordinate systems, and the complementary filtering is used for correcting the system speed prediction values and the position observation values according to the system speed observation values. By means of navigation fusion of the sensor values in three different coordinate systems, the upper-layer control logic can acquire more accurate low-delay sensor fusion values in different coordinate systems, control accuracy is improved, and response time is shortened.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty. In the drawings:
FIG. 1 is a schematic flow chart diagram illustrating a method for processing sensor data according to an embodiment of the present invention;
fig. 2 is a block diagram of a sensor data processing system according to an embodiment of the present invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description will be made with reference to the accompanying drawings. It is obvious that the drawings in the following description are only some examples of the invention, and that for a person skilled in the art, other drawings and embodiments can be derived from them without inventive effort.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
The first embodiment is as follows:
fig. 1 is a schematic flow chart of a sensor data processing method according to an embodiment of the present invention, and as shown in fig. 1, the method includes the following steps:
s1: and acquiring an acceleration value (recorded as imu _ acc) of the acceleration sensor and a position observed value of the sensor in an absolute coordinate system, a local coordinate system and a relative coordinate system.
In one embodiment, the method further comprises acquiring velocity observations and noise observations of the sensor in an absolute coordinate system, a local coordinate system, and a relative coordinate system.
Wherein the position observation includes: an absolute coordinate position observed value (denoted as pos _ abs), a relative coordinate position observed value (denoted as pos _ rel), and a local coordinate position observed value (denoted as pos _ loc); the velocity observations include: an absolute coordinate speed observation value (noted as vel _ abs), a relative coordinate speed observation value (noted as vel _ rel) and a local coordinate speed observation value (noted as vel _ loc); the noise observations include: absolute coordinate noise observations (denoted as abs _ noise), relative coordinate noise observations (denoted as rel _ noise), and local coordinate noise observations (denoted as loc _ noise).
S2: and converting the acceleration value into a geodetic coordinate system to obtain a geodetic coordinate acceleration value.
S3: and predicting the position observed values and the system speed under the three coordinate systems by using the geodetic coordinate acceleration value to obtain corresponding position predicted values and system speed predicted values under the three coordinate systems.
S4: and correcting the predicted value and the position observed value of the system speed according to the system speed observed value by utilizing complementary filtering.
In one embodiment, step S2 specifically includes:
s21: obtaining an acceleration value (recorded as acc _ body) of the body coordinate system according to the acceleration value imu _ acc and the acceleration offset value (recorded as acc _ offset);
and S22, obtaining a geodetic coordinate acceleration value (recorded as acc _ grd) according to the body coordinate acceleration value acc _ body by using the attitude rotation matrix (recorded as Rbg).
Expressed as:
acc_body＝imu_acc-acc_offset
acc_grd＝acc_body*Rbg
wherein the pose rotation matrix Rbg is used to identify the rotational relationship between the two coordinate systems, which may optionally be a 3x3 three-dimensional matrix.
After the geodetic coordinate acceleration value acc _ grd is obtained, the step S3 is carried out: according to the sampling time interval (marked as dt) of the acceleration sensor, predicting the lower position observed values and the system speed (marked as sys _ vel) of the three coordinate systems by using the earth coordinate acceleration value acc _ grd to obtain corresponding position predicted values and system speed predicted values of the three coordinate systems, wherein the prediction process is expressed as:
sys_pos_abs+＝sys_vel*dt+acc_grd*dt*dt*0.5
sys_pos_loc+＝sys_vel*dt+acc_grd*dt*dt*0.5
sys_pos_rel+＝sys_vel*dt+acc_grd*dt*dt*0.5
sys_vel+＝acc_grd*dt
the corresponding position prediction values under the three coordinate systems are respectively expressed as: the predicted value sys _ pos _ abs in the absolute coordinate system, the predicted value sys _ pos _ rel in the relative coordinate system, and the predicted value sys _ pos _ loc in the local coordinate system.
After the corresponding position predicted values and system speed predicted values under the three coordinate systems are obtained, a system speed observation value (marked as vel) is selected, in one implementation mode, a speed observation value of the coordinate system corresponding to the minimum noise observation value is selected as a system speed observation value, namely, the minimum value is selected from an absolute coordinate noise observation value abs _ noise, a relative coordinate noise observation value rel _ noise and a local coordinate noise observation value loc _ noise, for example, the absolute coordinate noise observation value abs _ noise is minimum, and then the absolute coordinate speed observation value vel _ abs is selected as the system speed observation value vel.
In one embodiment, step S4 performs correction processing on the system velocity prediction value sys _ vel and the position observation value from the system velocity observation value vel using complementary filtering.
The process of correcting the predicted value of the system speed is represented as:
vel_error＝vel-sys_vel
sys_vel+＝vel_error*Qv*dt
in one embodiment, the acceleration offset value is also corrected according to the system velocity observation value by using complementary filtering, and the correction process is represented as:
acc_offset_tmp+＝vel_error*Qa
acc_offset＝acc_offset_tmp*Rgb
the process of correcting the position observation includes:
sys_pos_abs+＝(pos_abs-sys_pos_abs)*Qpa*dt
sys_pos_loc+＝(pos_loc-sys_pos_loc)*Qpl*dt
sys_pos_rel+＝(pos_rel-sys_pos_rel)*Qpr*dt
wherein, qv, qa, qpa, qpl Qpr all represent debugging experience values, can be adjusted according to actual conditions, represent a weight, and the larger the value is, the stronger the correction force is, and the general value range thereof is 0-10.
The process realizes that the observed values under different coordinate systems measured by the sensor are corrected at the same time, the upper control logic can obtain more accurate fusion values of the low-delay sensor under different coordinate systems, the control precision is improved, and the response time is shortened.
The above process is illustrated below by way of a specific aircraft example.
For example, an aircraft is highly stabilized by using the height of a laser infrared distance meter in a relative coordinate system (the relative coordinate noise observed value measured in the relative coordinate system is 0.1, the smaller the value represents the smaller the noise, and the frequency is 100 Hz), and simultaneously an object is sought by using the UWB networking height in a local coordinate system (the local coordinate noise observed value measured in the local coordinate system is 0.5, and the frequency is 10 Hz), the measurement accuracy is insufficient and the response speed is slow in the related method due to the limitations of the UWB sensor noise in the local coordinate system of 0.5 and the frequency of 10 Hz.
At this time, in this embodiment, the system velocity observation value is corrected by using the differential velocity of the height of the laser infrared distance meter in the relative coordinate system, and the position observation value in the local coordinate system is fused by using the system velocity observation value, so that the navigation value noise observation value in the local coordinate system can be reduced from 0.5 to 0.1, and the frequency is increased from 10Hz to 100 Hz.
Specifically, the relative coordinate noise observed value of the laser infrared distance meter is 0.1, the relative coordinate speed observed value of the laser infrared distance meter is used as the system speed observed value, the noise of the system speed observed value is 0.1, then the position (namely the local coordinate position observed value) of the UWB is predicted by using the system speed observed value, the local coordinate noise observed value of the UWB is decreased from 0.5 to 0.1 of the UWB, the update frequency of the laser infrared distance meter (namely the relative coordinate system) is 100Hz, the update frequency of the system speed observed value is 100Hz by using the laser infrared distance meter as the system speed observed value reference, the update frequency of the UWB (namely the local coordinate system) is increased from 10Hz to 100Hz by using the system speed observed value, the update frequency of the UWB (namely the local coordinate system) represents one response time, the update frequency of the 100Hz represents 10ms, the system response time delay is decreased from 10 ns to 10ms by using the system speed observed value. And the noise observed value 0.1 can refer to an error of 0.1m, the noise 0.5 can refer to an error of 0.5m, and the method of the embodiment reduces the error from 0.5m to 0.1m, so that the error is reduced and the control precision is improved.
It should be understood that the above description is made by an aircraft, but this does not mean that the present embodiment can only be used for aircraft control, and other robot controls all that need to perform fusion control on multiple coordinate system data belong to the protection scope of the present embodiment.
The embodiment is used for navigation by simultaneously conducting navigation fusion on sensor values under three different coordinate systems, so that the upper-layer control logic can acquire more accurate low-delay sensor fusion values under different coordinate systems, the sensor fusion values are used for navigation, the control precision of the navigation can be improved, and the response time is shortened.
Example two:
the present embodiment provides a sensor data processing system, configured to execute the method according to the first embodiment, as shown in fig. 2, which is a structural block diagram of the sensor data processing system of the present embodiment, and includes:
the acquisition unit 100: the system comprises a sensor, a local coordinate system and a relative coordinate system, wherein the sensor is used for acquiring an acceleration value of the acceleration sensor and position observation values of the sensor in the absolute coordinate system, the local coordinate system and the relative coordinate system;
acceleration value conversion unit 200: the acceleration value is converted into a geodetic coordinate system to obtain a geodetic coordinate acceleration value;
the prediction unit 300: the system comprises a geodetic coordinate acceleration value module, a geodetic coordinate calculation module and a geodetic coordinate calculation module, wherein the geodetic coordinate acceleration value module is used for predicting the lower position observed values and the system speed of the three coordinate systems to obtain corresponding position predicted values and system speed predicted values of the three coordinate systems;
the correction unit 400: and the system is used for correcting the predicted value of the system speed and the position observed value by utilizing complementary filtering according to the system speed observed value.
The specific details of each unit module in the sensor data processing system have been described in detail in the sensor data processing method according to the first embodiment, and therefore are not described herein again.
In addition, the present invention also provides a sensor data processing apparatus comprising:
at least one processor, and a memory communicatively coupled to the at least one processor;
wherein the processor is configured to perform the method according to embodiment one by calling the computer program stored in the memory. A computer program, i.e. a program code for causing a sensor data processing device to perform the steps of the sensor data processing method as described in the above part of the present description of embodiments, when the program code is run on the sensor data processing device.
In addition, the present invention also provides a computer-readable storage medium, which stores computer-executable instructions for causing a computer to perform the method according to the first embodiment.
Without loss of generality, the computer-readable media may comprise computer storage media and communication media. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes RAM, ROM, EPROM, EEPROM, flash memory or other solid state memory technology, CD-ROM, DVD, or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices. Of course, those skilled in the art will appreciate that the computer storage media is not limited to the foregoing.
It should be noted that: the sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And specific embodiments thereof have been described above. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the system, the terminal, the storage medium and the system embodiment are substantially similar to the method embodiment, so that the description is simple, and the relevant points can be referred to the partial description of the method embodiment.
The above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same, although the present invention is described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (7)
1. A sensor data processing method, comprising:
acquiring an acceleration value of an acceleration sensor and position observation values of the sensor in an absolute coordinate system, a local coordinate system and a relative coordinate system, wherein the sensor is used for acquiring the position observation values;
converting the acceleration value into a geodetic coordinate system to obtain a geodetic coordinate acceleration value;
predicting the position observation values and the system speed under the three coordinate systems by using the geodetic coordinate acceleration values to obtain corresponding position predicted values and system speed predicted values under the three coordinate systems;
and correcting the predicted value of the system speed and the position observation value by utilizing complementary filtering according to the system speed observation value, wherein the speed observation value and the noise observation value of the sensor under an absolute coordinate system, a local coordinate system and a relative coordinate system are obtained, and the speed observation value of the coordinate system corresponding to the minimum noise observation value is selected as the system speed observation value.
2. The sensor data processing method of claim 1, wherein converting the acceleration value to a geodetic coordinate system yields a geodetic acceleration value, comprising:
obtaining a coordinate acceleration value of the machine body under a coordinate system of the machine body according to the acceleration value and the acceleration deviation value;
and obtaining the geodetic coordinate acceleration value according to the machine coordinate acceleration value by utilizing the attitude rotation matrix.
3. The sensor data processing method according to claim 1, wherein the geodetic acceleration value is used to predict the position observed value and the system velocity in three coordinate systems according to a sampling time interval of the acceleration sensor, so as to obtain corresponding predicted position values and predicted system velocity values in the three coordinate systems.
4. A method of sensor data processing according to claim 2, further comprising modifying the acceleration offset value from a system velocity observation using complementary filtering.
5. A sensor data processing system, comprising:
an acquisition unit: the device comprises a sensor, a control unit and a processing unit, wherein the sensor is used for acquiring an acceleration value of the acceleration sensor and a position observation value of the acceleration sensor under an absolute coordinate system, a local coordinate system and a relative coordinate system, and the sensor is used for acquiring the position observation value;
an acceleration value conversion unit: the acceleration value is converted into a geodetic coordinate system to obtain a geodetic coordinate acceleration value;
a prediction unit: the geodetic coordinate acceleration value is used for predicting the position observation value and the system speed under the three coordinate systems to obtain corresponding position predicted values and system speed predicted values under the three coordinate systems;
a correction unit: and the system is used for correcting the predicted value of the system speed and the position observation value according to the system speed observation value by utilizing complementary filtering, wherein the speed observation value and the noise observation value of the sensor in an absolute coordinate system, a local coordinate system and a relative coordinate system are obtained, and the speed observation value of the coordinate system corresponding to the minimum noise observation value is selected as the system speed observation value.
6. A sensor data processing device, comprising:
at least one processor; and a memory communicatively coupled to the at least one processor;
wherein the processor is adapted to perform the method of any one of claims 1 to 4 by invoking a computer program stored in the memory.
7. A computer-readable storage medium having stored thereon computer-executable instructions for causing a computer to perform the method of any one of claims 1 to 4.
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| CN109141410B (en) * | 2018-07-25 | 2020-09-01 | 深圳市集大自动化有限公司 | Multi-sensor fusion positioning method for AGV (automatic guided vehicle) combined navigation |
| CN110398251B (en) * | 2019-08-16 | 2021-02-09 | 北京邮电大学 | Trackless navigation AGV positioning system based on multi-sensor fusion and positioning method thereof |
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