CN113936044A - Method and device for detecting motion state of laser equipment, computer equipment and medium - Google Patents
Method and device for detecting motion state of laser equipment, computer equipment and medium Download PDFInfo
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- CN113936044A CN113936044A CN202111546010.1A CN202111546010A CN113936044A CN 113936044 A CN113936044 A CN 113936044A CN 202111546010 A CN202111546010 A CN 202111546010A CN 113936044 A CN113936044 A CN 113936044A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/277—Analysis of motion involving stochastic approaches, e.g. using Kalman filters
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C23/00—Combined instruments indicating more than one navigational value, e.g. for aircraft; Combined measuring devices for measuring two or more variables of movement, e.g. distance, speed or acceleration
Abstract
The embodiment of the invention discloses a method and a device for detecting the motion state of laser equipment, computer equipment and a medium. The method comprises the following steps: acquiring measurement data output by a sensor of laser equipment within preset time; inputting the measurement data into a preset Kalman filtering model to obtain the motion state of the laser equipment at each moment within the preset time; and detecting the motion state of the laser equipment within the preset time according to the range and the variance of the motion state. According to the invention, the sensor is configured on the laser equipment, and simultaneously Kalman filtering is carried out on the measurement data output by the sensor, so that the cost is low, the efficiency is higher, and the noise error caused by the laser equipment in a static state can be effectively eliminated, thereby accurately detecting whether the laser equipment is in the static state.
Description
Technical Field
The invention relates to the technical field of laser application, in particular to a method and a device for detecting the motion state of laser equipment, computer equipment and a medium.
Background
With the rapid development of electronic manufacturing industry, the traditional manufacturing process is more and more difficult to meet the requirements of modern electronic manufacturing process. Compared with the traditional processing technology, the laser processing technology has unique superiority and shows huge industrialization prospect.
At present, due to the shielding effect of a house structure, the state of the laser equipment cannot be accurately detected indoors through signals such as GPS and terrestrial magnetism when the laser equipment is used for carrying out laser processing indoors. Although the current state of the laser device can be obtained through technologies such as pure inertial navigation, laser radar, WiFi positioning, bluetooth beacon, ultra wide band and the like in the prior art, the method is high in cost, and the obtained data is low in precision, so that whether the laser device is in a static state or not cannot be accurately detected.
Disclosure of Invention
The embodiment of the invention provides a method and a device for detecting the motion state of laser equipment, computer equipment and a medium, which are used for solving the technical problem that the state of the laser equipment cannot be detected accurately at low cost in the prior art.
In a first aspect, an embodiment of the present invention provides a method for detecting a motion state of a laser device, where the method includes:
acquiring measurement data output by a sensor of laser equipment within preset time;
inputting the measurement data into a preset Kalman filtering model to obtain the motion state of the laser equipment at each moment within the preset time;
and detecting the motion state of the laser equipment within the preset time according to the range and the variance of the motion state.
In a second aspect, an embodiment of the present invention provides a detection apparatus for detecting a motion state of a laser device, including:
the first acquisition unit is used for acquiring measurement data output by a sensor of the laser equipment within preset time;
the first input unit is used for inputting the measurement data into a preset Kalman filtering model to obtain the motion state of the laser equipment at each moment within the preset time;
and the first detection unit is used for detecting the motion state of the laser equipment in the preset time according to the range and the variance of the motion state.
In a third aspect, an embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the method for detecting a motion state of a laser device according to the first aspect.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and the computer program, when executed by a processor, causes the processor to execute the method for detecting a motion state of a laser device according to the first aspect.
The embodiment of the invention provides a method and a device for detecting the motion state of laser equipment, computer equipment and a medium. The method includes the steps that a sensor is configured in the laser device, measurement data output by the laser device within preset time are obtained from the sensor, then the measurement data are input into a preset Kalman filtering model to obtain the motion state of the laser device within the preset time at each moment, and finally the motion state of the laser device within the preset time is detected according to the range difference and the variance of the motion state at each moment. According to the invention, the sensor is configured on the laser equipment, and simultaneously Kalman filtering is carried out on the measurement data output by the sensor, so that the cost is low, the efficiency is higher, and the noise error caused by the laser equipment in a static state can be effectively eliminated, thereby accurately detecting whether the laser equipment is in the static state.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flowchart of a method for detecting a motion state of a laser device according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a method for detecting a motion state of a laser device according to an embodiment of the present invention;
fig. 3 is another schematic flow chart of a method for detecting a motion state of a laser device according to an embodiment of the present invention;
fig. 4 is another schematic flow chart of a method for detecting a motion state of a laser device according to an embodiment of the present invention;
fig. 5 is another schematic flow chart of a method for detecting a motion state of a laser device according to an embodiment of the present invention;
fig. 6 is another schematic flow chart of a method for detecting a motion state of a laser device according to an embodiment of the present invention;
fig. 7 is a schematic block diagram of a detection apparatus for detecting a motion state of a laser device according to an embodiment of the present invention;
FIG. 8 is a schematic block diagram of a computer device provided by an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. 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.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that 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. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
Referring to fig. 1, fig. 1 is a schematic flow chart illustrating a method for detecting a motion state of a laser device according to an embodiment of the present invention. The method for detecting the motion state of the laser equipment is applied to the terminal equipment, and the method for detecting the motion state of the laser equipment is executed through a detection system of the motion state of the laser equipment installed in the terminal equipment. The terminal device has a data processing function and can receive measurement data output by the sensor, such as a desktop computer, a notebook computer, a tablet computer, or a mobile phone.
The method for detecting the motion state of the laser device will be described in detail below.
As shown in FIG. 1, the method includes the following steps S110 to S130.
And S110, acquiring measurement data output by a sensor of the laser equipment within preset time.
Specifically, the preset time is time information that the terminal device needs to detect a motion state of the laser device at any time within the preset time, for example, when the terminal device needs to detect a current motion state of the laser device, the last time in the preset time is the current time.
In this embodiment, the sensor mounted in the laser device is an IMU sensor having a gyroscope, and the sensor is configured with a three-axis gyroscope, a three-axis accelerometer, and a three-axis magnetometer. The measurement data output by the sensor comprises high and low data in the three-dimensional direction, the high and low data comprise acceleration, angular velocity and angle of the laser device at each moment in the three-dimensional direction, the precision of the acceleration is 0.0005g, the precision of the angular velocity is 0.61 degrees, and the precision of the angle is 0.1 degrees.
In other embodiments of the present invention, before step S110, the method further includes the steps of: presetting the baud rate for transmitting the measurement data and initializing the baud rate.
In this embodiment, the terminal device and the sensor of the laser device are connected by a USB or a serial port for data communication, and in order to ensure the stability of communication between the terminal device and the sensor and reduce the baud rate error between the terminal device and the sensor, the baud rate at which the sensor transmits the measurement data needs to be preset, and the sensor initializes the baud rate in advance before transmitting the measurement data.
And S120, inputting the measurement data into a preset Kalman filtering model to obtain the motion state of the laser equipment at each moment in the preset time.
Specifically, the kalman filtering model is constructed by using a kalman filtering algorithm, wherein the kalman filtering algorithm is an algorithm for performing optimal estimation on a system state by using a linear system state equation and inputting and outputting observation data through a system. The Kalman filtering algorithm is composed of five formulas, and the five formulas are prediction and updating.
Wherein the prediction equation is:
wherein the content of the first and second substances,
the estimated value of the prior state at the moment k is the data observed in the sensor;
posterior state estimation for time k-1The evaluation value is one of the final output results of Kalman filtering,
and
are state variables, and F is a state transfer function, and is actually a guess model for the target state transition. For example, in moving target tracking, a state transition matrix is often used to model the motion of a target, the model may be uniform linear motion or uniform accelerated motion, and when the state transition matrix does not conform to the state transition model of the target, filtering may quickly diverge; b and u are system control variables, i.e. matrices that convert inputs to states,
estimating covariance for k moment prior, which is the intermediate calculation result of filtering; p is the posterior estimation covariance of the k-1 moment, represents the uncertainty of the state, and is one of the results of filtering; q is a process noise matrix and this parameter is used to represent the error between the state transition matrix and the actual process.
The update equation is:
where y is the residual of the actual and predicted observations, and Kalman gain oneCorrecting the prior (prediction) to obtain a posterior; z is the measured mean, which is the input to the filtering;
the posterior state estimation value at the moment k is one of filtering results, namely an updated result, namely optimal estimation;
estimating covariance for the posteriori at time k, one of the results of the filtering; h is a measurement function, is a conversion matrix from the state variable to the measurement, represents the relationship connecting the state and the observation, is a linear relationship in Kalman filtering, and is responsible for converting the m-dimensional measurement value to n-dimensional measurement value so as to be in accordance with the mathematical form of the state variable, and is one of the preconditions of filtering; r is measurement noise, a known condition of the filter; k is a Kalman gain matrix, which is a filtering intermediate calculation result and is also called Kalman gain or Kalman coefficient; i is the identity matrix.
In this embodiment, the state variable of the kalman filter model includes an angular velocity of the laser device, the laser device is a laser device that can be held by a user, and when the user holds the laser device to continuously move, the acceleration of the laser device is similar to that of the laser device in a stationary state due to the small movement velocity of the laser device, so that the movement state of the laser device needs to be detected by the angular velocity of the laser device when the laser device moves. Therefore, when the kalman filter model is constructed, the motion speed in the state variable of the kalman filter model needs to be replaced by the angular speed of the laser device, so that the actual angular speed of the laser device at each moment can be obtained from the kalman filter model after the angular speed of the laser device is input into the kalman filter model.
In other inventive embodiments, as shown in fig. 2, step S120 includes sub-steps S121 and S122.
S121, analyzing the measurement data to obtain the acceleration, the angle and the angular speed measured by the sensor at each moment;
and S122, inputting the acceleration, the angle and the angular speed into the Kalman filtering model to obtain the motion state of the laser equipment at each moment.
In this embodiment, the measurement data includes high and low data in a three-dimensional direction, and at this time, the measurement data cannot be directly input into five equations in a kalman filter model for calculation, so that the measurement data needs to be analyzed to obtain the acceleration, the angle, and the angular velocity measured by the sensor at each moment from the measurement data. In the measurement data, the acceleration AxH and AxL are respectively high-bit data and low-bit data of the laser device in the X-axis direction, the AyH and AyL are respectively high-bit data and low-bit data of the laser device in the Y-axis direction, and the AzH and AzL are respectively high-bit data and low-bit data of the laser device in the Z-axis direction; WxH and WxL of the angular velocity in the measured data are respectively high-bit data and low-bit data of the laser equipment in the X-axis direction, WyH and WyL are respectively high-bit data and low-bit data of the laser equipment in the Y-axis direction, and WzH and WzL are respectively high-bit data and low-bit data of the laser equipment in the Z-axis direction; the RollH and the RollL of the angle in the measured data are respectively high-order data and low-order data of the laser equipment in the X-axis direction, the Pitch H and the Pitch L are respectively high-order data and low-order data of the laser equipment in the Y-axis direction, and the YawH and the YawL are respectively high-order data and low-order data of the laser equipment in the Z-axis direction.
Specifically, the calculation formula of the acceleration is as follows:
ax=((AxH<<8)|AxL)/32768*16g
ay=((AyH<<8)|AyL)/32768*16g
az=((AzH<<8)|AzL)/32768*16g
wherein g is the local gravitational acceleration, and ax, ay and az are the accelerations of the laser device on the X axis, the Y axis and the Z axis after the analysis, respectively.
The angular velocity is calculated by the formula:
Wx=((wxH<<8)|wxL)/32768*2000(°/s)
Wy=((wyH<<8)|wyL)/32768*2000(°/s)
Wz=((wzH<<8)|wzL)/32768*2000(°/s)
wherein Wx, Wy and Wz are angular velocities of the laser device on X, Y and Z axes after the analysis, respectively.
The angle calculation formula is as follows:
Roll=((RollH<<8)|RollL)/32768*180(°)
Pitch=((PitchH<<8)|PitchL)/32768*180(°)
Yaw=((YawH<<8)|YawL)/32768*180(°)
the Roll angle Roll, the Pitch angle Pitch and the Yaw angle Yaw are the rotational angles of the laser device on the X axis, the Y axis and the Z axis after the analysis.
In other inventive embodiments, as shown in FIG. 3, step S121 includes sub-steps S1211 and S1212.
S1211, obtaining a checksum of the measurement data;
and S1212, if the measurement data is matched with the checksum, generating the acceleration, the angle and the angular velocity measured by the sensor at each moment according to the measurement data.
In particular, the checksum is a sum used in the field of data processing and data communication for checking a set of data items of a destination, and is usually expressed in hexadecimal notation. In order to ensure the integrity and accuracy of the measurement data output by the sensor, whether the measurement data transmitted by all the sensors is acquired or not needs to be verified according to the checksum of the measurement data after transmission. If the measurement data transmitted by all the sensors is acquired, the acceleration, the angle and the angular velocity measured by the sensors at each moment can be calculated according to the corresponding calculation formula. For example, when the high-low data containing the acceleration of the laser device in the measurement data is checked and matched, the check Sum is: sum =0X55+0X51+ AxH + AxL + AyH + AyL + AzH + AzL, and when the checksum Sum thereof matches the high and low data containing the acceleration of the laser device in the measurement data, the acceleration of the laser device on the X axis, the Y axis and the Z axis is generated according to the data.
In other inventive embodiments, as shown in FIG. 4, step S122 includes sub-steps S1221, S1222, and S1223.
S1221, generating a net acceleration of the laser equipment according to the angle and the acceleration;
s1222, generating state variables of the Kalman filtering model according to the angular speed and the net acceleration;
and S1223, generating the motion state of the laser equipment at each moment in the Kalman filtering model according to the state variables.
Specifically, the net acceleration of the laser device is obtained by subtracting the acceleration of gravity from the laser device, and the state variable in the kalman filter model is X = (Wx, Wy, Wz, Ax, Ay, Az), where (Wx, Wy, Wz) is an angular velocity analyzed from the measurement data, and (Ax, Ay, Az) is the net acceleration of the laser device.
In this embodiment, quaternion conversion is performed on the angle, the gravitational acceleration of the laser device is projected according to the converted quaternion, then the projected gravitational acceleration is subtracted from the analyzed acceleration, so that the net acceleration of the laser device at each moment can be obtained, and then the net acceleration is input into a kalman filter model, so that the motion state of the laser device at each moment can be obtained, wherein the motion state is the actual motion state of the laser device at each moment, and is characterized by the angular velocity of the laser device.
In other inventive embodiments, as shown in fig. 5, step S1221 includes sub-steps S12211, S12212, and S12213.
S12211, carrying out quaternion conversion on the angle to obtain a converted quaternion;
s12212, projecting the gravity acceleration of the laser equipment according to the converted quaternion to obtain the projected gravity acceleration;
and S12213, generating the net acceleration of the laser equipment according to the acceleration and the projected gravitational acceleration.
In this embodiment, the quaternary conversion formula of the angle is:
q(0)=cos(Pitch/2)*cos(Roll/2)*cos(Yaw/2)-sin(Pitch/2)*sin(Roll/2)*sin(Yaw/2)
q(1)=sin(Pitch/2)*cos(Roll/2)*cos(Yaw/2)-cos(Pitch/2)*sin(Roll/2)*sin(Yaw/2)
q(2)=cos(Pitch/2)*sin(Roll/2)*cos(Yaw/2)+Sin(Pitch/2)*cos(Roll/2)*sin(Yaw/2)
q(3)=cos(Pitch/2)*cos(Roll/2)*sin(Yaw/2)+cos(Pitch/2)*sin(Roll/2)*sin(Yaw/2)
the formula for projecting the converted quaternion to the gravity acceleration of the laser device is as follows:
gx=2*q(1)*q(3)-2q(0)*q(2)
gy=2*q(2)*q(3)+2q(0)*q(1)
gz=q(0)2-q(1)2-q(2)2+q(3)2
wherein gx, gy and gz are the gravitational acceleration of the laser device after the gravitational acceleration is projected on the X axis, the Y axis and the Z axis.
The final resulting net acceleration is formulated as:
Ax=ax-gx
Ay=ay-gy
Az=az-gz
and S130, detecting the motion state of the laser equipment in the preset time according to the range and the variance of the motion state.
Specifically, the motion state includes a slow movement state, a violent motion state, and a stationary state, the motion state is determined by the angular velocity of the laser device, the range of the motion state is a difference between a maximum value and a minimum value of the actual angular velocity of the laser device within a preset time, and the variance of the motion state is a variance of the actual angular velocity of the laser device within the preset time. The extreme difference of the motion state is used for representing the discrete degree of the actual angular speed of the laser device in the preset time, namely the fluctuation degree or the sudden change degree of the laser device in the preset time, and the variance of the motion state is used for representing the deviation degree of the actual angular speed of the laser device in the preset time. In the embodiment, the range and the variance of the motion state of the laser device within the preset time are combined to detect the motion state of the laser device within the preset time, so that the accuracy of detecting the motion state of the laser device within the preset time is further improved.
In other inventive embodiments, as shown in fig. 6, step S130 includes sub-steps S131 and S132.
S131, if the range is larger than a preset threshold value, detecting the motion state of the laser equipment within the preset time according to the range;
and S132, if the range is smaller than the threshold, detecting the motion state of the laser equipment within the preset time according to the variance.
Specifically, the threshold is a critical value for selecting the range and the variance of the motion state when detecting the motion state of the laser device within the preset time, and the threshold may be set according to practical applications, which is not specifically limited in this embodiment.
In this embodiment, the range of the motion state is represented by the following formula:
max (wi) is a function of taking a maximum value in a preset time, min (wi) is a function of taking a minimum value in the preset time, and Thresh1 is a process of verifying the Kalman filtering state.
The variance formula of the motion state is as follows:
wherein std (wi) is a standard deviation function taken within a preset time, Thresh2 is a process for verifying the Kalman filtering state, and wi is an actual angular velocity at each moment within the preset time.
In addition, when the range of the motion state of the laser device is smaller than the threshold value within the preset time, after the variance is adopted to detect that the laser device is in the static state, the state variable in the kalman filtering model needs to be initialized, so that the situation that the kalman filtering is continuously performed in the laser device under the static state condition is prevented, and therefore errors caused by the noise in the static state are eliminated.
In the method for detecting the motion state of the laser device provided by the embodiment of the invention, the measurement data output by a sensor of the laser device within the preset time is obtained; inputting the measurement data into a preset Kalman filtering model to obtain the motion state of the laser equipment at each moment within the preset time; and detecting the motion state of the laser equipment within the preset time according to the range and the variance of the motion state. According to the method, the sensor is configured on the laser equipment, and simultaneously Kalman filtering is performed on the measurement data output by the sensor, so that the technical problem that the state of the laser equipment cannot be accurately detected indoors is solved.
The embodiment of the invention also provides a detection device 100 for the motion state of the laser equipment, which is used for executing any embodiment of the detection method for the motion state of the laser equipment.
Specifically, referring to fig. 7, fig. 7 is a schematic block diagram of a detection apparatus 100 for detecting a motion state of a laser device according to an embodiment of the present invention.
As shown in fig. 7, the apparatus 100 for detecting the motion state of the laser device includes: a first acquisition unit 110, a first input unit 120, and a first detection unit 130.
The first obtaining unit 110 is configured to obtain measurement data output by a sensor of the laser device within a preset time.
In another embodiment, the apparatus 100 for detecting the motion state of the laser device includes: a setting unit.
And the setting unit is used for presetting the baud rate for transmitting the measurement data and initializing the baud rate.
The first input unit 120 is configured to input the measurement data into a preset kalman filter model, so as to obtain a motion state of the laser device at each time within the preset time.
In another embodiment, the first input unit 120 includes: the device comprises an analysis unit and a second input unit.
The analysis unit is used for analyzing the measurement data to obtain the acceleration, the angle and the angular velocity measured by the sensor at each moment; and the second input unit is used for inputting the acceleration, the angle and the angular speed into the Kalman filtering model to obtain the motion state of the laser equipment at each moment.
In another embodiment, the parsing unit includes: a second acquisition unit and a first generation unit.
The second acquisition unit is used for acquiring the check sum of the measurement data; and the first generating unit is used for generating the acceleration, the angle and the angular velocity measured by the sensor at each moment according to the measurement data if the measurement data is matched with the checksum.
In another embodiment, the second input unit includes: a second generation unit, a third generation unit, and a fourth generation unit.
The second generating unit is used for generating the net acceleration of the laser equipment according to the angle and the acceleration; a third generating unit, configured to generate a state variable of the kalman filter model according to the angular velocity and the net acceleration; and the fourth generating unit is used for generating the motion state of the laser equipment at each moment in the Kalman filtering model according to the state variable.
In another embodiment, the second generating unit includes: the device comprises a conversion unit, a projection unit and a fifth generation unit.
The conversion unit is used for carrying out quaternion conversion on the angle to obtain a converted quaternion; the projection unit is used for projecting the gravitational acceleration of the laser equipment according to the converted quaternion to obtain the projected gravitational acceleration; and the fifth generating unit is used for generating the net acceleration of the laser equipment according to the acceleration and the projected gravitational acceleration.
A first detecting unit 130, configured to detect a motion state of the laser device within the preset time according to the range and the variance of the motion state.
In another embodiment, the first detection unit 130 includes: a second detection unit and a third detection unit.
The second detection unit is used for detecting the motion state of the laser equipment within the preset time according to the range if the range is larger than a preset threshold; and the third detection unit is used for detecting the motion state of the laser equipment within the preset time according to the variance if the range is smaller than the threshold.
The detection apparatus 100 for the motion state of the laser device provided by the embodiment of the present invention is configured to perform the above-mentioned obtaining of the measurement data output by the sensor of the laser device within a preset time; inputting the measurement data into a preset Kalman filtering model to obtain the motion state of the laser equipment at each moment within the preset time; and detecting the motion state of the laser equipment within the preset time according to the range and the variance of the motion state.
It should be noted that, as can be clearly understood by those skilled in the art, the detailed implementation process of the detection apparatus 100 for detecting the motion state of the laser device and each unit may refer to the corresponding description in the foregoing method embodiment, and for convenience and brevity of description, no further description is provided herein.
The detection means of the motion state of the laser device may be implemented in the form of a computer program that can be run on a computer device as shown in fig. 8.
Referring to fig. 8, fig. 8 is a schematic block diagram of a computer device according to an embodiment of the present application. The computer device 500 may be a terminal, wherein the terminal may be an electronic device with a communication function, such as a smart phone, a tablet computer, a notebook computer, a desktop computer, a personal digital assistant, and a wearable device.
Referring to fig. 8, the computer device 500 includes a processor 502, memory, and a network interface 505 connected by a system bus 501, where the memory may include a non-volatile storage medium 503 and an internal memory 504.
The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 comprises program instructions that, when executed, cause the processor 502 to perform a method of detecting a motion state of a laser device.
The processor 502 is used to provide computing and control capabilities to support the operation of the overall computer device 500.
The internal memory 504 provides an environment for running the computer program 5032 in the non-volatile storage medium 503, and when the computer program 5032 is executed by the processor 502, the processor 502 may be enabled to execute a method for detecting a motion state of the laser device.
The network interface 505 is used for network communication with other devices. Those skilled in the art will appreciate that the configuration shown in fig. 8 is a block diagram of only a portion of the configuration relevant to the present teachings and does not constitute a limitation on the computer device 500 to which the present teachings may be applied, and that a particular computer device 500 may include more or less components than those shown, or combine certain components, or have a different arrangement of components.
Wherein the processor 502 is configured to run the computer program 5032 stored in the memory to implement the following steps: acquiring measurement data output by a sensor of laser equipment within preset time; inputting the measurement data into a preset Kalman filtering model to obtain the motion state of the laser equipment at each moment within the preset time; and detecting the motion state of the laser equipment within the preset time according to the range and the variance of the motion state.
In an embodiment, before the obtaining of the measurement data output by the laser device within the preset time, the processor 502 specifically implements the following steps: presetting the baud rate for transmitting the measurement data and initializing the baud rate.
In an embodiment, when the processor 502 inputs the measurement data into a preset kalman filter model to obtain the motion state of the laser device at each time within the preset time, the following steps are specifically implemented: analyzing the measurement data to obtain the acceleration, the angle and the angular speed measured by the sensor at each moment; and inputting the acceleration, the angle and the angular speed into the Kalman filtering model to obtain the motion state of the laser equipment at each moment.
In an embodiment, when the processor 502 implements the analysis of the measurement data to obtain the acceleration, the angle, and the angular velocity measured by the sensor at each time, the following steps are specifically implemented: acquiring a checksum of the measurement data; and if the measurement data is matched with the checksum, generating the acceleration, the angle and the angular speed measured by the sensor at each moment according to the measurement data.
In an embodiment, when the processor 502 inputs the acceleration, the angle, and the angular velocity into the kalman filter model to obtain the motion state of the laser device at each time, the following steps are specifically implemented: generating a net acceleration of the laser device according to the angle and the acceleration; generating a state variable of the Kalman filtering model according to the angular speed and the net acceleration; and generating the motion state of the laser equipment at each moment in the Kalman filtering model according to the state variables.
In an embodiment, when the processor 502 implements the generating of the net acceleration of the laser device according to the angle and the acceleration, the following steps are specifically implemented: carrying out quaternion conversion on the angle to obtain a converted quaternion; projecting the gravitational acceleration of the laser equipment according to the converted quaternion to obtain the projected gravitational acceleration; and generating the net acceleration of the laser equipment according to the acceleration and the projected gravitational acceleration.
In an embodiment, when the processor 502 detects the motion state of the laser device within the preset time according to the range and the variance of the motion state, the following steps are specifically implemented: if the range is larger than a preset threshold value, detecting the motion state of the laser equipment within the preset time according to the range; and if the range is smaller than the threshold value, detecting the motion state of the laser equipment within the preset time according to the variance.
It should be understood that, in the embodiment of the present Application, the Processor 502 may be a Central ProcesSing Unit (CPU), and the Processor 502 may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
It will be understood by those skilled in the art that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program instructing associated hardware. The computer program includes program instructions, and the computer program may be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the flow steps of the embodiments of the method described above.
Accordingly, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program comprises program instructions. The program instructions, when executed by the processor, cause the processor to perform the steps of: acquiring measurement data output by a sensor of laser equipment within preset time; inputting the measurement data into a preset Kalman filtering model to obtain the motion state of the laser equipment at each moment within the preset time; and detecting the motion state of the laser equipment within the preset time according to the range and the variance of the motion state.
In an embodiment, before the processor executes the program instructions to obtain the measurement data output by the laser device within the preset time, the processor specifically implements the following steps: presetting the baud rate for transmitting the measurement data and initializing the baud rate.
In an embodiment, when the processor executes the program instruction to input the measurement data into a preset kalman filter model to obtain the motion state of the laser device at each time within the preset time, the following steps are specifically implemented: analyzing the measurement data to obtain the acceleration, the angle and the angular speed measured by the sensor at each moment; and inputting the acceleration, the angle and the angular speed into the Kalman filtering model to obtain the motion state of the laser equipment at each moment.
In an embodiment, when the processor executes the program instructions to analyze the measurement data to obtain the acceleration, the angle, and the angular velocity measured by the sensor at each moment, the following steps are specifically implemented: acquiring a checksum of the measurement data; and if the measurement data is matched with the checksum, generating the acceleration, the angle and the angular speed measured by the sensor at each moment according to the measurement data.
In an embodiment, when the processor executes the program instruction to input the acceleration, the angle, and the angular velocity into the kalman filter model to obtain the motion state of the laser device at each time, the following steps are specifically implemented: generating a net acceleration of the laser device according to the angle and the acceleration; generating a state variable of the Kalman filtering model according to the angular speed and the net acceleration; and generating the motion state of the laser equipment at each moment in the Kalman filtering model according to the state variables.
In an embodiment, when the processor executes the program instructions to generate the net acceleration of the laser device according to the angle and the acceleration, the processor specifically implements the following steps: carrying out quaternion conversion on the angle to obtain a converted quaternion; projecting the gravitational acceleration of the laser equipment according to the converted quaternion to obtain the projected gravitational acceleration; and generating the net acceleration of the laser equipment according to the acceleration and the projected gravitational acceleration.
In an embodiment, when the processor executes the program instructions to detect the motion state of the laser device within the preset time according to the range and the variance of the motion state, the following steps are specifically implemented: if the range is larger than a preset threshold value, detecting the motion state of the laser equipment within the preset time according to the range; and if the range is smaller than the threshold value, detecting the motion state of the laser equipment within the preset time according to the variance.
The storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk, which can store various computer readable storage media.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative. For example, the division of each unit is only one logic function division, and there may be another division manner in actual implementation. For example, various elements or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented.
The steps in the method of the embodiment of the invention can be sequentially adjusted, combined and deleted according to actual needs. The units in the device of the embodiment of the invention can be merged, divided and deleted according to actual needs. In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a terminal, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method for detecting the motion state of laser equipment is characterized by comprising the following steps:
acquiring measurement data output by a sensor of laser equipment within preset time;
inputting the measurement data into a preset Kalman filtering model to obtain the motion state of the laser equipment at each moment within the preset time;
and detecting the motion state of the laser equipment within the preset time according to the range and the variance of the motion state.
2. The method for detecting the motion state of the laser device according to claim 1, further comprising, before the obtaining the measurement data output by the laser device within a preset time:
presetting the baud rate for transmitting the measurement data and initializing the baud rate.
3. The method for detecting a motion state of a laser device according to claim 1, wherein the inputting the measurement data into a preset kalman filter model to obtain the motion state of the laser device at each time within the preset time includes:
analyzing the measurement data to obtain the acceleration, the angle and the angular speed measured by the sensor at each moment;
and inputting the acceleration, the angle and the angular speed into the Kalman filtering model to obtain the motion state of the laser equipment at each moment.
4. The method for detecting the motion state of the laser device according to claim 3, wherein the analyzing the measurement data to obtain the acceleration, the angle, and the angular velocity measured by the sensor at each time comprises:
acquiring a checksum of the measurement data;
and if the measurement data is matched with the checksum, generating the acceleration, the angle and the angular speed measured by the sensor at each moment according to the measurement data.
5. The method for detecting a motion state of a laser device according to claim 3, wherein the inputting the acceleration, the angle, and the angular velocity into the kalman filter model to obtain the motion state of the laser device at each time includes:
generating a net acceleration of the laser device according to the angle and the acceleration;
generating a state variable of the Kalman filtering model according to the angular speed and the net acceleration;
and generating the motion state of the laser equipment at each moment in the Kalman filtering model according to the state variables.
6. The method for detecting the motion state of the laser device according to claim 5, wherein the generating the net acceleration of the laser device according to the angle and the acceleration comprises:
carrying out quaternion conversion on the angle to obtain a converted quaternion;
projecting the gravitational acceleration of the laser equipment according to the converted quaternion to obtain the projected gravitational acceleration;
and generating the net acceleration of the laser equipment according to the acceleration and the projected gravitational acceleration.
7. The method for detecting the motion state of the laser device according to claim 1, wherein the detecting the motion state of the laser device within the preset time according to the range and the variance of the motion state comprises:
if the range is larger than a preset threshold value, detecting the motion state of the laser equipment within the preset time according to the range;
and if the range is smaller than the threshold value, detecting the motion state of the laser equipment within the preset time according to the variance.
8. A detection device for a motion state of a laser device is characterized by comprising:
the first acquisition unit is used for acquiring measurement data output by a sensor of the laser equipment within preset time;
the first input unit is used for inputting the measurement data into a preset Kalman filtering model to obtain the motion state of the laser equipment at each moment within the preset time;
and the first detection unit is used for detecting the motion state of the laser equipment in the preset time according to the range and the variance of the motion state.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the method for detecting a motion state of a laser device according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method of detecting a state of motion of a laser device according to any one of claims 1 to 7.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114140362A (en) * | 2022-01-29 | 2022-03-04 | 杭州微影软件有限公司 | Thermal imaging image correction method and device |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101078627A (en) * | 2007-06-28 | 2007-11-28 | 北京航空航天大学 | On-line calibration method for shield machine automatic guiding system based on optical fiber gyro and PSD laser target |
| CN101726295A (en) * | 2008-10-24 | 2010-06-09 | 中国科学院自动化研究所 | Unscented Kalman filter-based method for tracking inertial pose according to acceleration compensation |
| CN102903162A (en) * | 2012-09-24 | 2013-01-30 | 清华大学 | Automobile running state information acquisition system and method |
| CN106500695A (en) * | 2017-01-05 | 2017-03-15 | 大连理工大学 | A kind of human posture recognition method based on adaptive extended kalman filtering |
| WO2017175844A1 (en) * | 2016-04-06 | 2017-10-12 | ヤマハ発動機株式会社 | Orientation estimation device and transport equipment |
| CN109001787A (en) * | 2018-05-25 | 2018-12-14 | 北京大学深圳研究生院 | A kind of method and its merge sensor of solving of attitude and positioning |
| CN109001488A (en) * | 2018-04-26 | 2018-12-14 | 深圳市有为信息技术发展有限公司 | A kind of detection method and detection system of the stationary motion of vehicle location monitoring |
| CN111102978A (en) * | 2019-12-05 | 2020-05-05 | 深兰科技（上海）有限公司 | Method and device for determining vehicle motion state and electronic equipment |
| CN111551174A (en) * | 2019-12-18 | 2020-08-18 | 无锡北微传感科技有限公司 | High-dynamic vehicle attitude calculation method and system based on multi-sensor inertial navigation system |
| CN112083726A (en) * | 2020-09-04 | 2020-12-15 | 湖南大学 | Park-oriented automatic driving double-filter fusion positioning system |
-
2021
- 2021-12-17 CN CN202111546010.1A patent/CN113936044B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101078627A (en) * | 2007-06-28 | 2007-11-28 | 北京航空航天大学 | On-line calibration method for shield machine automatic guiding system based on optical fiber gyro and PSD laser target |
| CN101726295A (en) * | 2008-10-24 | 2010-06-09 | 中国科学院自动化研究所 | Unscented Kalman filter-based method for tracking inertial pose according to acceleration compensation |
| CN102903162A (en) * | 2012-09-24 | 2013-01-30 | 清华大学 | Automobile running state information acquisition system and method |
| WO2017175844A1 (en) * | 2016-04-06 | 2017-10-12 | ヤマハ発動機株式会社 | Orientation estimation device and transport equipment |
| CN106500695A (en) * | 2017-01-05 | 2017-03-15 | 大连理工大学 | A kind of human posture recognition method based on adaptive extended kalman filtering |
| CN109001488A (en) * | 2018-04-26 | 2018-12-14 | 深圳市有为信息技术发展有限公司 | A kind of detection method and detection system of the stationary motion of vehicle location monitoring |
| CN109001787A (en) * | 2018-05-25 | 2018-12-14 | 北京大学深圳研究生院 | A kind of method and its merge sensor of solving of attitude and positioning |
| CN111102978A (en) * | 2019-12-05 | 2020-05-05 | 深兰科技（上海）有限公司 | Method and device for determining vehicle motion state and electronic equipment |
| CN111551174A (en) * | 2019-12-18 | 2020-08-18 | 无锡北微传感科技有限公司 | High-dynamic vehicle attitude calculation method and system based on multi-sensor inertial navigation system |
| CN112083726A (en) * | 2020-09-04 | 2020-12-15 | 湖南大学 | Park-oriented automatic driving double-filter fusion positioning system |
Non-Patent Citations (1)
| Title |
|---|
| 贾亮等: "基于BP神经网络的人体运动姿态识别", 《电脑与信息技术》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114140362A (en) * | 2022-01-29 | 2022-03-04 | 杭州微影软件有限公司 | Thermal imaging image correction method and device |
| CN114140362B (en) * | 2022-01-29 | 2022-07-05 | 杭州微影软件有限公司 | Thermal imaging image correction method and device |
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| Publication number | Publication date |
|---|---|
| CN113936044B (en) | 2022-03-18 |
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