CN114217628A - Double-path IMU unit unmanned aerial vehicle controller based on 5G communication and control method - Google Patents
Double-path IMU unit unmanned aerial vehicle controller based on 5G communication and control method Download PDFInfo
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Abstract
The invention provides a two-way IMU (inertial measurement unit) unmanned aerial vehicle controller based on 5G communication and a control method, wherein the two-way IMU unmanned aerial vehicle controller comprises an embedded processing unit, a 5G communication module, a power supply voltage stabilizing module, a GPS (global positioning system) module, a geomagnetic sensor module and two sets of IMU sensor modules, wherein the two sets of IMU sensor modules are arranged in a manner of Y, Z axis opposite directions and in a mirror symmetry mode with the same X axis direction; the method comprises the steps of IMU sensor module detection, acquisition and calibration of geomagnetic sensor module detection data, acquisition and processing of two paths of IMU detection data, and calculation of the attitude angle of the unmanned aerial vehicle through an extended Kalman filtering algorithm based on the acquired data. According to the invention, the errors caused by temperature and long-time integration are corrected by complementation of two groups of IMU units, so that the influence of the errors on the unmanned aerial vehicle flight controller is effectively weakened, and the stability of the unmanned aerial vehicle is improved.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle control, in particular to a two-way IMU unit unmanned aerial vehicle controller based on 5G communication and a control method.
Background
With the development of the unmanned aerial vehicle technology, the unmanned aerial vehicle has wide applications in the fields of aerial photography, agriculture, plant protection, miniature self-shooting, express transportation, disaster relief, wild animal observation, infectious disease monitoring, surveying and mapping, news reporting, power inspection, disaster relief, movie and television shooting, romantic manufacturing and the like, gradually enters the lives of people, and an Inertial Measurement Unit (IMU) is an important component of the unmanned aerial vehicle, is mainly used for measuring the three-axis attitude angle or angular velocity and the acceleration of an object, and is generally integrated in an unmanned aerial vehicle flight controller.
However, at present, the unmanned aerial vehicle flight controller can only carry out data communication and interaction in a wired connection mode such as USB, USART, I2C and the like, and cannot carry out effective autonomous control; an IMU unit used for attitude detection in flight control is a single-group IMU unit, so that the unmanned aerial vehicle is easily interfered in the flight process; on the other hand, the temperature drift generated by the IMU unit may also cause inaccuracy of estimation of the self attitude of the drone over time.
Disclosure of Invention
In order to solve the problems, the invention provides a two-way IMU unit unmanned aerial vehicle controller based on 5G communication and a control method, wherein the controller adopts a 5G module to realize attitude control in a wireless communication mode, is provided with two IMU units simultaneously, carries out algorithm processing by recording parameter changes of the two IMU units, corrects errors generated by temperature based on complementation of the two IMU units, effectively weakens the influence of the errors generated by temperature change on the unmanned aerial vehicle flight controller, and improves the stability of the unmanned aerial vehicle.
The invention provides a double-path IMU unit unmanned aerial vehicle controller based on 5G communication, which has the following specific technical scheme:
including embedded processing unit, 5G communication module, power steady voltage module, GPS module, earth magnetism sensor module and two sets of IMU sensor module, it is two sets of IMU sensor module respectively with embedded processing unit connects, just embedded processing unit with 5G communication module connects, and is two sets of IMU sensor module is Z axle opposite direction, and the same mirror symmetry setting of X, Y axle direction.
Further, a CAN communication module, a serial communication module and an I2The C communication module and the SPI communication module are connected with the embedded processing unit and are provided with corresponding hardware interfaces, and the CAN communication modules are provided with two CAN communication modules.
The invention also provides a two-way IMU unit unmanned aerial vehicle control method based on 5G communication, which is based on the unmanned aerial vehicle controller and specifically comprises the following steps:
s1: detecting whether the IMU sensor module is abnormal or not, if so, performing complementary filtering processing through double-path IMU detection data to adjust the flight attitude, and if so, executing return operation;
s2: acquiring detection data of the geomagnetic sensor module, calibrating, recording and storing;
s3: acquiring feedback signals of two groups of IMU sensor modules, and performing filtering processing to obtain acceleration data and angular velocity data, wherein the acceleration data and the angular velocity data are acceleration and angular velocity of the IMU sensor modules in different axial directions;
s4: respectively carrying out fusion processing and integral processing on the acceleration data and the angular velocity data obtained after the filtering processing;
s5: and taking the data after the fusion processing and the integral processing and the detection data of the calibrated geomagnetic sensor module as input, calculating the attitude angle of the unmanned aerial vehicle through an extended Kalman filtering algorithm, and outputting the attitude angle.
Further, in step S1, the detection by the IMU sensor module includes the following specific steps:
acquiring detection data of the two groups of IMU sensor modules, judging whether the IMU sensor modules are abnormal or not according to the detection data, if so, uploading fault information through the USB communication module and the CAN communication module, calculating an attitude angle of the unmanned aerial vehicle through an extended Kalman filtering algorithm based on the data of the normally working IMU sensor modules and the data of the geomagnetic sensor, judging the course of the unmanned aerial vehicle, and executing return operation;
and calculating to obtain an absolute value difference value of the detection data of the two IMU sensor modules, comparing the absolute value difference value with a preset value, and when the absolute value difference value exceeds the preset value, connecting a 5G module with a server end to push fault information and returning through a GPS module.
Further, in step S3, the acquiring of the acceleration data and the angular velocity data specifically includes:
s301: acquiring acceleration and angular velocity acquired by a set number of adjacent time acquisition nodes according to acquisition frequency, and forming an acceleration data set and an angular velocity data set according to different axial directions;
s302: and carrying out mean processing on the data in the acceleration data set and the angular velocity data set, and respectively obtaining acceleration data and angular velocity data of different axial directions of each IMU sensor corresponding to the acceleration data set and the angular velocity data set.
Further, in step S302, before the averaging process, the method further includes:
and respectively carrying out bucket sorting processing on the data in the acceleration data set and the angular velocity data set, and removing at least one maximum acceleration data, at least one angular velocity data and at least one minimum acceleration data and at least one angular velocity data.
Further, the filtering process uses a notch filter to perform the filtering process, which specifically includes:
where s is the frequency of the input signal, ωnTo trap the frequency, delta1、δ2The notch coefficient.
Further, the notch coefficient is obtained by calculating a notch frequency, the notch frequency is a motor commutation frequency of the unmanned aerial vehicle, and the specific calculation is as follows:
where Depth is the notch Depth and Δ f is the difference in the notch frequency range.
The invention has the following beneficial effects:
1. be equipped with two way IMUs, be mirror symmetry setting on the two sides of unmanned aerial vehicle controller circuit board, carry out complementary filtering through the data of two way IMUs collection and handle, weaken because the influence of the error that the temperature variation produced to the controller, improved the stability of controller, guarantee simultaneously under the condition of external factor interference, can be accurate predict unmanned aerial vehicle's flight gesture.
2. The controller adopts the communication and the transmission of 5G communication module realization data, is convenient for introduce outside remote control, has improved the stability of unmanned aerial vehicle flight in-process communication.
Drawings
FIG. 1 is a schematic diagram of the controller architecture of the present invention;
FIG. 2 is a schematic flow diagram of the method of the present invention;
FIG. 3 is a schematic diagram of the relative position of two IMUs according to the present invention.
Detailed Description
In the following description, technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
Embodiment 1 of the invention discloses a two-way IMU unit unmanned aerial vehicle controller based on 5G communication, as shown in figure 1,
the intelligent detection system comprises an embedded processing unit, a 5G communication module, a power supply voltage stabilizing module, a GPS module, a geomagnetic sensor module and two groups of IMU sensor modules, wherein the IMU sensor modules are an IMU sensor module 1 and an IMU sensor module 2 respectively, and are connected with the embedded processing unit respectively, the embedded processing unit is connected with the 5G communication module, and the two groups of IMU sensor modules are arranged in a mirror symmetry mode with opposite directions of Y, Z shafts and the same direction of an X shaft;
as shown in fig. 3, promptly IMU sensor module installs all the way in the front of unmanned aerial vehicle controller circuit board, installs up, and IMU unit installs at the back of unmanned aerial vehicle controller all the way, installs down, keeps X axle positive direction unanimous, and Y, Z axle positive direction is opposite, and X and Y axle are the axial of unmanned aerial vehicle horizontal plane, and the Z axle is the axial of unmanned aerial vehicle vertical plane, X, Y, Z axle mutually perpendicular.
In this embodiment, the controller further comprises a CAN communication module, a serial communication module, and an I2The communication module C and the SPI communication module are connected with the embedded processing unit and are provided with corresponding hardware interfaces, two CAN communication modules are arranged, and the serial communication module adopts a USB3.0 module circuit;
the controller is also provided with an isolation circuit and a level conversion circuit, the embedded processing unit is respectively connected with each module through the level conversion circuit and the isolation circuit, and the power supply voltage stabilizing module is provided with two first power supply voltage stabilizing modules and two second power supply voltage stabilizing modules which are respectively connected with the embedded processing unit and each module to provide stable voltage input.
In this embodiment, the flight controller is provided with a metal shell, that is, the control hardware circuit is placed in a closed metal cavity, so as to effectively reduce external electromagnetic interference and electromagnetic radiation of the flight controller.
The embedded processing unit adopts a GD32 chip as a processor and is used for acquiring information such as unmanned aerial vehicle postures in real time and realizing autonomous control of the unmanned aerial vehicle.
The level conversion circuit is used for converting different level protocols of modules into levels effective to the embedded processing unit through the level conversion chip for inputting because different level protocols exist in each external chip.
The isolation circuit is used for ensuring the stability of the embedded processing unit, ensuring that the embedded processing unit and other devices are not influenced when the external devices are accidentally broken down, and protecting each path of devices in the circuit to the maximum extent.
Said I2A C communication module for communication connection with two IMU sensor modules and peripheral sensor access
And the IMU sensor module is used for detecting the attitude of the unmanned aerial vehicle, monitoring the attitude of the unmanned aerial vehicle in real time and transmitting data into the embedded processor unit.
5G communication module for unmanned aerial vehicle and outside realize communication, realize remote control and real time monitoring's module, help realizing unmanned aerial vehicle's management and control.
And the serial port communication module is used for preliminary debugging of the unmanned aerial vehicle controller, inputting of the GPS module and converting of the CAN communication protocol.
CAN mouth communication module for unmanned aerial vehicle controller expands other sensors outward.
And the SPI communication module is used for an interface for externally expanding and storing the embedded processing unit.
Example 2
The embodiment 2 of the invention discloses a two-way IMU unit unmanned aerial vehicle control method based on 5G communication based on the embodiment 1, and the method is based on the unmanned aerial vehicle controller in the embodiment 1; the two groups of IMU sensor modules are respectively an IMU1 and an IMU2, when the unmanned aerial vehicle is overlooked, the IMU1 is on the top, and the IMU2 is on the bottom;
the acceleration and the angular velocity in the X-axis direction measured by the IMU1 and the IMU2 are consistent in positive and negative, the change directions of the numerical values are the same, the acceleration value of the flight controller in the X-axis direction can be obtained approximately through the difference value of the sum of the acceleration and the angular velocity, ax is (a1X + a2X)/2, ax represents the acceleration value of the unmanned aerial vehicle in the X-axis direction, and a1X and a2X represent the acceleration values in the X-axis direction detected by the IMU1 and the IMU2 respectively;
the parameters of acceleration and angular velocity in the Y-axis direction measured by IMU1 and IMU2 are opposite, and can be said that when a1Y >0 and a2Y <0, looking down at the drone at this time, the drone is subjected to a force to the left, i.e., ay > 0; conversely, when a1y is less than 0 and a2y is greater than 0, the unmanned aerial vehicle is overlooked, and is subjected to a rightward force, namely ay is less than 0; wherein ay represents an acceleration value of the drone in the Y-axis direction, and a1Y, a2Y represent acceleration values of the IMU1 and IMU2, respectively, in the Y-axis direction; the acceleration of the unmanned aerial vehicle on the Y axis is recorded as ay ═ (a1Y-a 2Y)/2;
the acceleration of the IMU1 and IMU2 in the Z-axis direction is represented as az ═ 2/2 (a1Z + a2Z), a1Z and a2Z respectively represent the acceleration values of the IMU1 and IMU2 in the Z-axis direction, since the two acceleration increasing directions of the drone in the Z-axis direction are the same, but since the accelerometer of the Z-axis is essentially measuring pressure, the pressure is right up for the IMU1, the pressure is on the bottom, the acceleration measured at rest is g, and the acceleration measured at rest is-g for the IMU2, that is, in this embodiment, the acceleration value of the Z-axis is measured at rest when flight control is 0.
Based on the above, as shown in fig. 2, in this embodiment, the control method specifically includes the following steps:
s1: the embedded processing unit creates an IMU detection thread and detects parameters fed back by the IMU1 and the IMU 2;
judging whether the IMU sensor module is abnormal or not according to the detection data, if so, uploading fault information through the USB communication module and the CAN communication module, calculating the attitude angle of the unmanned aerial vehicle through an extended Kalman filtering algorithm based on the data of the normally working IMU sensor module and the data of the geomagnetic sensor, judging the course of the unmanned aerial vehicle, and executing return operation;
and calculating to obtain an absolute value difference value of the detection data of the two IMU sensor modules, comparing the absolute value difference value with a preset value, and when the absolute value difference value exceeds the preset value, connecting a 5G module with a server end to push fault information and returning through a GPS module.
S2: acquiring detection data of the geomagnetic sensor module, calibrating, recording and storing;
s3: acquiring acceleration data and angular velocity data of two groups of IMU sensor modules, and performing filtering processing, wherein the acceleration data and the angular velocity data are acceleration and angular velocity of the IMU sensor modules in different axial directions;
a thread is newly established by the embedded processing unit for acquiring IMU data, and in this embodiment, the acquisition frequency is set to 100 HZ;
because the adopted brushless motor is generally in close coupling connection with the arm of the unmanned aerial vehicle, in the flying process of the unmanned aerial vehicle, the brushless motor can generate magnetic field interference and motor vibration with certain frequency by high-frequency reversing, and therefore the interference mixed with the part is filtered by detecting the rotating speed of the unmanned aerial vehicle and carrying out trap treatment;
inputting the acquired data signal into a notch filter for filtering, wherein the process is as follows:
where s is the frequency of the input signal, ωnTo trap the frequency, delta1、δ2The notch coefficient.
The notch coefficient is obtained by calculating notch frequency, the notch frequency is the motor reversing frequency of the unmanned aerial vehicle, and the specific calculation is as follows:
wherein Depth is the notch Depth, and Δ f is the difference of the notch frequency range;
the motor reversing frequency is obtained by calculating the motor rotating speed, and the specific calculation formula is as follows: f is n P/60, wherein n is the motor speed (revolution/minute) and P is the number of magnetic poles;
the acquired data signals are filtered to obtain acceleration data and angular velocity data, 12 linked list spaces of 1 × 2 bytes are opened up by the embedded processing unit and are respectively marked as a1x, a1y, a1z, ω 1x, ω 1y, ω 1z, a2x, a2y, a2z, ω 2x, ω 2y and ω 2z, and the acceleration of X, Y, Z axis of IMU1, the angular velocity of X, Y, Z axis of IMU1, the acceleration of X, Y, Z axis of IMU2 and the angular velocity of X, Y, Z axis of IMU2 are respectively saved.
S3: respectively carrying out fusion processing and integral processing on the obtained acceleration data and angular velocity data;
the fusion treatment is as follows:
s4: and taking the data after fusion processing and integral processing and the detection data of the calibrated geomagnetic sensor module as input, calculating and outputting the attitude angle of the unmanned aerial vehicle through an extended Kalman filtering algorithm, and realizing the attitude control of the unmanned aerial vehicle.
Example 3
Embodiment 3 of the present invention discloses a two-way IMU unit unmanned aerial vehicle control method based on 5G communication, based on embodiment 2, in step S3, performing mean processing by acquiring multiple sets of acceleration and angular velocity data to obtain acceleration data and angular velocity data input by performing posture processing, and the specific process is as follows:
s301: acquiring acceleration and angular velocity acquired by 10 adjacent time acquisition nodes according to acquisition frequency, and forming an acceleration data set and an angular velocity data set according to different axial directions, namely acquiring 10 continuous groups of acceleration and angular velocity data acquired by IMU1 and IMU2 to form a corresponding data set;
the embedded processing unit opens up 12 linked list spaces of 20 × 2Byte to store the acceleration data set and the angular velocity data set;
and (3) carrying out bucket sorting processing on 10 data in each group and storing the data into an original chain table, and removing two maximum and two minimum values in each group.
S302: and respectively carrying out mean value processing on six data obtained after the bucket sorting processing and the maximum and minimum values of each group are removed, solving the mean value of each group, and opening up 12 linked list spaces of 1 × 2Byte for storage.
The invention is not limited to the foregoing embodiments. The invention extends to any novel feature or any novel combination of features disclosed in this specification and any novel method or process steps or any novel combination of features disclosed.
Claims (8)
1. The utility model provides a double-circuit IMU unit unmanned aerial vehicle controller based on 5G communication, its characterized in that, including embedded processing unit, 5G communication module, power steady voltage module, GPS module, geomagnetic sensor module and two sets of IMU sensor module, two sets of IMU sensor module respectively with embedded processing unit connects, just embedded processing unit with 5G communication module connects, and is two sets of IMU sensor module is Y, Z axle opposite direction, and the same mirror symmetry of X axle direction sets up.
2. The UAV controller of claim 1, further comprising a CAN communication module, a serial communication module, and an I2The C communication module and the SPI communication module are connected with the embedded processing unit and are provided with corresponding hardware interfaces, and the CAN communication modules are provided with two CAN communication modules.
3. A control method of a two-way IMU unit unmanned aerial vehicle based on 5G communication is based on the unmanned aerial vehicle controller of any one of claims 1-2, and is characterized by comprising the following steps:
s1: detecting whether the IMU sensor module is abnormal or not, if so, performing complementary filtering processing through double-path IMU detection data to adjust the flight attitude, and if so, executing return operation;
s2: acquiring detection data of the geomagnetic sensor module, calibrating, recording and storing;
s3: acquiring feedback signals of two groups of IMU sensor modules, and performing filtering processing to obtain acceleration data and angular velocity data, wherein the acceleration data and the angular velocity data are acceleration and angular velocity of the IMU sensor modules in different axial directions;
s4: respectively carrying out fusion processing and integral processing on the acceleration data and the angular velocity data obtained after the filtering processing;
s5: and taking the data after the fusion processing and the integral processing and the detection data of the calibrated geomagnetic sensor module as input, calculating the attitude angle of the unmanned aerial vehicle through an extended Kalman filtering algorithm, and outputting the attitude angle.
4. The unmanned aerial vehicle control method of claim 3, wherein in step S1, the IMU sensor module detects the following steps:
acquiring detection data of the two groups of IMU sensor modules, judging whether the IMU sensor modules are abnormal or not according to the detection data, if so, uploading fault information through the USB communication module and the CAN communication module, calculating an attitude angle of the unmanned aerial vehicle through an extended Kalman filtering algorithm based on the data of the normally working IMU sensor modules and the data of the geomagnetic sensor, judging the course of the unmanned aerial vehicle, and executing return operation;
and calculating to obtain an absolute value difference value of the detection data of the two IMU sensor modules, comparing the absolute value difference value with a preset value, and when the absolute value difference value exceeds the preset value, connecting a 5G module with a server end to push fault information and returning through a GPS module.
5. The method for controlling the two-way IMU unit drone of claim 4, wherein in step S3, the obtaining of the acceleration data and the angular velocity data is specifically:
s301: acquiring acceleration and angular velocity acquired by a set number of adjacent time acquisition nodes according to acquisition frequency, and forming an acceleration data set and an angular velocity data set according to different axial directions;
s302: and carrying out mean processing on the data in the acceleration data set and the angular velocity data set, and respectively obtaining acceleration data and angular velocity data of different axial directions of each IMU sensor corresponding to the acceleration data set and the angular velocity data set.
6. The dual-channel IMU unit drone control method of claim 5, further comprising, before the averaging process in step S302:
and respectively carrying out bucket sorting processing on the data in the acceleration data set and the angular velocity data set, and removing at least one maximum acceleration data, at least one angular velocity data and at least one minimum acceleration data and at least one angular velocity data.
7. The dual-channel IMU unit unmanned aerial vehicle control method of any of claims 4 or 6, wherein the filtering process uses a notch filter for filtering, and specifically comprises the following steps:
where s is the frequency of the input signal, ωnTo trap the frequency, delta1、δ2The notch coefficient.
8. The method of claim 7, wherein the notch coefficient is calculated from a notch frequency, the notch frequency being a motor commutation frequency of the drone, and the following is specifically calculated:
where Depth is the notch Depth and Δ f is the difference in the notch frequency range.
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