CN113916260A - Automatic adjustment calculation method for real-time networking of measuring robot - Google Patents
Automatic adjustment calculation method for real-time networking of measuring robot Download PDFInfo
- Publication number
- CN113916260A CN113916260A CN202111163239.7A CN202111163239A CN113916260A CN 113916260 A CN113916260 A CN 113916260A CN 202111163239 A CN202111163239 A CN 202111163239A CN 113916260 A CN113916260 A CN 113916260A
- Authority
- CN
- China
- Prior art keywords
- meteorological
- real
- monitoring
- observation
- intelligent
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
- G01B21/32—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring the deformation in a solid
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Manufacturing & Machinery (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Testing Or Calibration Of Command Recording Devices (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method for calculating the automatic adjustment of real-time networking of a measuring robot. The method comprises the following steps: establishing an intelligent measuring station, establishing a reference point and establishing a monitoring point; step two: laying meteorological acquisition points and acquiring meteorological data; step three: acquiring angles and distances in real time; step four: performing real-time meteorological correction; step five: calculating approximate coordinates of monitoring points, determining the weights of observation angles and distances, and establishing an angle and distance error equation; step six: composition and solution of a normal equation; step seven: calculating errors in the point positions of the monitoring points; step eight: and repeating the step two meteorological data acquisition and the step seven monitoring point position error calculation to acquire the monitoring point coordinates of the second period. The invention has the advantages of improved stability, high precision and high efficiency of the deformation monitoring.
Description
Technical Field
The invention relates to the technical field of surveying and mapping, in particular to a method for automatically calculating adjustment of real-time networking of a measuring robot.
Background
The measuring robot is an intelligent electronic total station with automatic searching, automatic accurate aiming and reading functions. And the coordinate information of the target point can be calculated by utilizing the measuring robot by acquiring the angle and the distance of the target point relative to the measuring station. At present, a polar coordinate measuring system consisting of a single measuring robot utilizes multiple real-time difference technologies and the like, and is well applied to projects such as water conservancy and hydropower projects, bridges, tunnels and the like. However, a single measuring robot is limited by the visibility condition and the maximum target identification distance, and therefore, the single measuring robot can only be used for deformation monitoring of a deformation body with good visibility condition and a small deformation area, and is low in monitoring precision and low in monitoring speed.
Therefore, it is necessary to develop a method for monitoring deformation of a deformable body, which has high monitoring accuracy and high monitoring speed and satisfies various visual conditions and various deformation regions.
Disclosure of Invention
The invention aims to provide a real-time networking automatic adjustment calculation method for a measuring robot, so that the stability and the precision of an automatic deformation monitoring technology of the measuring robot are improved, the monitoring efficiency is improved, and various visibility conditions and deformation monitoring of deformation bodies in various deformation areas are met; the method overcomes the defects that the automatic monitoring of a single measuring robot in the prior art only adopts a polar coordinate method, and the precision is limited by the through-viewing condition and the maximum target identification distance.
In order to achieve the purpose, the technical scheme of the invention is as follows: a real-time networking automatic adjustment calculation method for a measurement robot is characterized by comprising the following steps: as shown in fig. 4, includes the steps of,
the method comprises the following steps: establishing an intelligent measuring station, establishing a reference point and establishing a monitoring point;
establishing an intelligent testing station: establishing a plurality of intelligent test stations (more than or equal to 2) on a stable foundation according to the test area condition to form an intersection network, wherein the established intelligent test stations are all provided with a set of automatic observation systems of the measuring robots;
establishing a reference point: the method comprises the following steps of uniformly establishing stable reference points according to the conditions of a measurement area, wherein a set of single prism group which is over against an intelligent measurement station is arranged on the established reference points, forced centering devices of prisms are embedded into a concrete observation pier, and the direction and distance from the intelligent measurement station to each reference point cover the whole measurement area, so that the method is most beneficial to real-time meteorological correction and real-time differential correction;
establishing a monitoring point: monitoring points are uniformly distributed on a monitoring object deformation body according to the section, one or more sets of single prism groups or 360-degree prism groups facing the intelligent measuring station are arranged on the established monitoring points, and forced centering devices of the prisms are embedded in the concrete observation pier;
step two: laying meteorological acquisition points and acquiring meteorological data;
arranging meteorological acquisition points on the intelligent measuring station and the reference point, and arranging meteorological acquisition points on representative monitoring points arranged on the deformation body according to the cross section;
the distributed meteorological acquisition points are uniformly provided with independently developed atmospheric temperature and humidity intelligent measuring instruments (namely meteorological sensors) for acquiring temperature, humidity and atmospheric pressure meteorological factors in real time;
step three: real-time angle and distance acquisition
Opening all intelligent stations to automatically open and close the windows, and after 30min, starting measurement by the intelligent temperature, humidity and air pressure measuring instrument to obtain meteorological data, detecting weather conditions and judging whether severe weather such as rain, fog and the like exists or not; if yes, continuously measuring and detecting the weather conditions through temperature, humidity and air pressure intelligent measurement; otherwise, controlling a plurality of measuring robots to start observation by an autonomous research and development observation software system to obtain a real-time observation value (namely a real-time angle and a real-time distance); judging whether the real-time observation value exceeds the limit and whether the lack of the measurement condition exists, and if the real-time observation value exceeds the limit and/or the lack of the measurement condition exists, returning to the state that the plurality of measurement robots are controlled to restart the observation through the autonomous research and development observation software system; if the real-time observation value is not out of limit and no lack of measurement condition exists, storing the real-time observation value (namely the real-time angle and the distance) into an original measurement value library;
the method for controlling the observation of a plurality of measuring robots by the autonomous research and development observation software system comprises the following steps: an autonomous research and development observation software system controls a measurement robot on an intelligent measurement station to automatically find a reference point and a monitoring point target, clockwise observation is carried out, and a real-time angle and distance observation value (namely a real-time meteorological correction factor) is obtained;
step four: performing real-time meteorological correction;
acquiring real-time meteorological correction factors, and performing real-time meteorological correction on the distance observed value of the measuring robot;
the real-time meteorological correction method comprises a meteorological space interpolation method and a meteorological aberration correction method;
the meteorological difference correction method is characterized in that a temperature, humidity and air pressure intelligent measuring instrument is used for acquiring corrected meteorological factors in real time, a temperature, humidity and air pressure meteorological model of a measuring area is established, meteorological values at monitoring points of non-distributed meteorological acquisition points are interpolated, the meteorological factors are used for correcting distance observation values from an intelligent measuring station to the monitoring points, and the distance measurement precision is improved;
the change values generated between the intelligent survey station and the reference point in different periods are used as meteorological factor influence values to correct the distance observation value between the intelligent survey station and the monitoring point, namely meteorological difference correction, so that the distance measurement precision is improved; selecting a reference point with good representativeness to carry out meteorological difference correction;
the invention applies the meteorological station interpolation and meteorological differential correction to real-time meteorological correction to improve the distance measurement precision;
step five: calculating approximate coordinates of monitoring points, determining the weights of observation angles and distances, and establishing an angle and distance error equation;
calculating approximate coordinates of monitoring points: calculating approximate coordinates of the monitoring points by using the geometric relation between the real-time observation values;
determine weights for observation angle and distance: determining the weights of the observation angle and the distance according to the precision of the observation angle and the distance;
establishing an angle and distance error equation: data preprocessing is carried out, observation data of all robots are obtained, an angle and distance error equation is determined according to the established geometric relationship between the observation values, and networking adjustment calculation is carried out;
step six: composition and solution of a normal equation;
establishing a method equation and resolving the method equation according to a least square method by using the established error equation to obtain two-dimensional coordinates of each monitoring point;
step seven: calculating errors in the point positions of the monitoring points;
calculating errors in the point positions of the monitoring points, wherein the errors in the point positions are used for evaluating the coordinate precision of the monitoring points calculated in the sixth step;
judging whether the errors in the point positions of the monitoring points exceed the limit, if so, jumping to the step three, and controlling a plurality of measuring robots to start observation through an autonomous research and development observation software system; otherwise, closing all the intelligent measuring stations and opening and closing the windows, stopping measuring by the intelligent temperature, humidity and air pressure measuring instrument (namely a meteorological sensor), completing monitoring of the first period, and inputting the monitoring result into an achievement compilation library;
step eight: and repeating the step two meteorological data acquisition to the step seven monitoring point position error calculation, and acquiring the monitoring point coordinate of the next period (namely the nth period), wherein n is more than or equal to 2.
In the above technical solution, in step three, as shown in fig. 5, a specific control method for autonomously developing and observing a software system for controlling a measurement robot on an intelligent survey station is as follows:
s31: starting control of the measuring robot;
s32: setting an observation precision grade, an observation return number and a limit difference value, and selecting a zero direction point;
s33: setting a meteorological acquisition interval and starting to acquire meteorological data;
s34: controlling the measuring robot to observe the horizontal angle clockwise;
s35: determining whether the horizontal angle of step S34 is out of limit;
when the horizontal angle exceeds the limit, jumping to step S34;
when the horizontal angle does not exceed the limit, jumping to step S36;
s36: controlling the measuring robot to observe the side length and the vertical angle clockwise;
s37: determining whether the side length and the vertical angle in the S36 are over-limit and whether a lack-of-measurement condition exists;
when the side length and the vertical angle exceed the limits and/or the lack of the detection exists, the step S36 is skipped;
and when the side length and the vertical angle are not out of limits and no missing measurement condition exists, ending the control, inputting the monitoring result (namely the acquired real-time angle and distance) into an original measurement value library, and switching to the next step (namely switching to the fourth step).
The autonomous research and development observation software system for controlling the measuring robot on the intelligent measuring station meets the standard use requirement. The measuring robot in the invention is an intelligent electronic total station with automatic searching, automatic accurate aiming and reading functions; the invention connects the measuring robot with the computer through the modern communication technology, the autonomous research and development observation software system for controlling the measuring robot on the intelligent measuring station realizes the automation of the measuring process, data recording, data processing and report output, is high-precision intelligent deformation monitoring software based on a plurality of measuring robots, realizes the remote intelligent control of a plurality of measuring networking robots, enables the stations of the measuring robots to be mutually matched and coordinate networking operation, realizes the unattended automatic measurement, has the intelligent judgment and processing functions on the target shielding, and improves the monitoring precision and the monitoring speed.
The autonomous research and development observation software system is the sub-software of the networking automatic adjustment software system adopted by the real-time networking automatic adjustment calculation method of the measuring robot (the autonomous research and development observation software system has the functions of real-time meteorological correction, approximate coordinate calculation, error equation establishment, real-time networking adjustment calculation, precision evaluation and error calculation in point positions). The networking automatic adjustment software system comprises a real-time meteorological correction module, an approximate coordinate calculation module, an error equation establishment module, a real-time networking adjustment calculation module, a precision evaluation module and a point location error calculation module; the real-time meteorological correction module is used for carrying out real-time meteorological correction; the approximate coordinate calculation module is used for calculating the approximate coordinates of the monitoring points; the error equation establishing module is used for establishing an angle and distance error equation; the real-time networking adjustment calculation module is used for calculating two-dimensional coordinates of the monitoring points; the precision evaluation module is used for evaluating the coordinate precision of the monitoring point; and the point location error calculation module is used for calculating the point location error of the monitoring point.
In the technical scheme, the independently developed intelligent measuring instrument for the atmospheric temperature, the humidity and the pressure comprises a main control circuit board and a sensor component; the peripheries of the main control circuit board and the sensor component are provided with an integrated radiation-proof cover; the independently developed intelligent measuring instrument for the atmospheric temperature, humidity and pressure adopts a small radiation-proof cover integrated design, so that the volume is reduced;
the master control circuit board comprises a singlechip, a crystal oscillator circuit, a battery, a linear voltage stabilizer and a Bluetooth template;
a temperature sensor, a humidity sensor and an air pressure sensor are integrated on the sensor component; the independently developed intelligent measuring instrument for the atmospheric temperature and the humidity has high integration level and reduced volume, and adopts a dormant design, so that the power consumption of the independently developed intelligent measuring instrument for the atmospheric temperature and the humidity is reduced by about 80 percent;
the battery is connected with the linear voltage stabilizer to form a stable power supply; the battery power supply with the floating voltage becomes a stable power supply with the voltage of 3.3V after flowing through the linear voltage stabilizer;
the linear voltage stabilizer is respectively connected with the temperature sensor, the humidity sensor, the air pressure sensor, the singlechip and the Bluetooth template; the stable power supply is connected to the sensor part, the singlechip and the Bluetooth module and supplies power to the sensor part, the singlechip and the Bluetooth module;
the Bluetooth template is connected with the single chip microcomputer;
the crystal oscillator circuit is connected with the singlechip, and the crystal oscillator circuit is connected with the singlechip and provides a clock for the singlechip;
the singlechip is respectively connected with the temperature sensor, the humidity sensor and the air pressure sensor.
In the technical scheme, the singlechip is provided with singlechip built-in software;
the singlechip built-in software C comprises a singlechip initialization module, an SHT30-IIC communication protocol module, an analog-to-digital conversion acquisition module, an SPI communication protocol module and an MODBUS protocol module;
the single chip microcomputer initialization module, the SHT30-IIC communication protocol module, the analog-to-digital conversion acquisition module, the SPI communication protocol module and the MODBUS protocol module are sequentially connected;
the independently developed intelligent measuring instrument for the atmospheric temperature, humidity and pressure controls a highly integrated sensor component through built-in software of a single chip microcomputer arranged on the single chip microcomputer, so that real-time data monitoring of the sensor component is realized, the measurement precision of the sensor component is improved, the measurement precision of the sensor component is about 0.1% for atmospheric pressure, and the measurement precision of the sensor component is about 3% RH for humidity.
In the technical scheme, an I2C interface is arranged on the singlechip;
the temperature sensor and the humidity sensor are both provided with an I2C interface; the singlechip is communicated with the temperature sensor and the humidity sensor through an I2C communication protocol module; an I2C interface of the singlechip is connected with I2C interfaces of the temperature sensor and the humidity sensor to acquire temperature and humidity data; the I2C bus occupies less pin resources, so that the independently developed intelligent measuring instrument for atmospheric temperature, humidity and pressure is convenient to miniaturize and miniaturize, the size is reduced, the cost is reduced, and the power consumption is reduced;
the single chip microcomputer is provided with an SPI interface; an SPI interface is arranged on the air pressure sensor; the single chip microcomputer is communicated with the air pressure sensor through an SPI communication protocol module; the SPI interface of singlechip and baroceptor's SPI interface connection gather atmospheric pressure data, improve transmission speed.
In the technical scheme, a UART interface is arranged on the singlechip;
a UART interface is arranged on the Bluetooth template; the UART interface of the singlechip is connected with the UART interface of the Bluetooth module, and the acquired data is transmitted to the Bluetooth module;
the Bluetooth module can transmit data to an upper computer (such as a mobile phone, a computer and the like);
the single chip microcomputer is communicated with an upper computer (such as a mobile phone, a computer and the like) through an MODBUS protocol module, so that the application range and the adaptation scene of the independently developed intelligent atmosphere temperature and humidity measuring instrument are improved; the Modbus is an industrial standard protocol, can be directly connected with a PLC (programmable logic controller), an acquisition instrument, configuration software and the like for communication, and can also be connected with other host computers (upper computers) compatible with the Modbus protocol;
the independently developed intelligent measuring instrument for the atmospheric temperature, humidity and pressure adopts a modular structure design, and the functions of the display recording module can be completed by a mobile phone, so that the use is convenient, and the cost is reduced; the bluetooth wireless design, operator distance sensor more than 1 meter avoids interference such as human heat source, improves measurement accuracy.
The atmosphere temperature and humidity pressure intelligent measuring instrument of independently developing integrates three kinds of sensors of temperature sensor, humidity transducer and baroceptor simultaneously, realizes that temperature, humidity, the simultaneous high accuracy of atmospheric pressure measurations, transmits through the bluetooth mode, the low-power consumption, convenient to carry, and the integrated level is high, and the specification is unified, simple structure, preparation processing is simple, but batch production, and is with low costs, the consumption is little, small, the measuring value is accurate to have overcome prior art's environment measuring instrument shortcoming with high costs, the structure is complicated, the consumption is big.
In the technical scheme, in the fourth step, real-time meteorological factor acquisition and real-time correction of the distance observation value of the measuring robot are carried out;
the method for weather correction further comprises correcting the observed value of the distance between the intelligent survey station and the monitoring point by using the changes generated between the intelligent survey station and the reference point in different periods, namely weather difference correction.
In the technical scheme, in the fifth step, the approximate coordinates of the monitoring points are calculated and obtained by adopting automatic approximate calculation;
as shown in fig. 1, the method of approximate coordinate automatic approximation is as follows:
the calculation of the approximate coordinates of the unknown points is to find out angle information meeting the calculation conditions from the observation data, namely, a rear view point i and a station j corresponding to the observation angle are known points, a front view point k is angle information of the unknown points, and the automatic approximate coordinates calculation algorithm of the monitoring points is as follows:
step S11: starting calculation;
step S12: traversing all angle observation data, and searching angle observation values of which the observation station and the rear viewpoint are known points and the front viewpoint is an unknown point;
step S13: extracting coordinates of two points from the coordinate data set according to the station j and the rear view point i, obtaining a coordinate azimuth angle of a rear view side through coordinate inverse calculation, and obtaining a coordinate azimuth angle of a front view side by adding an observation angle (the azimuth angle needs to be ensured to be a true coordinate azimuth angle);
step S14: extracting the forward-looking side length S from the side length array according to the site j and the forward-looking point k, and calculating to obtain the coordinate of the forward-looking point k based on the forward-looking side coordinate azimuth angle, the observation side length S and the coordinate value of the site;
the points of which the initial coordinate calculation is finished are regarded as known points and added into a known point list, and the points of which the calculation is finished are removed from an unknown point list;
step S15: determining whether the approximate coordinates of all unknown points are calculated;
when the approximate coordinates of all the unknown points are not calculated, jumping to step S12;
and when all the unknown point approximate coordinates are calculated, the calculation is finished.
In the above technical solution, in step five, the weights of the corners and the edges are determined (the method for determining the weights of the corners and the edges is the prior art);
if n is observed in the corner net1Angle n of2Length of one side, then
If it is not
Then
While
In the above technical solution, in step five, an error equation is constructed (the method for constructing the error is the prior art):
measuring the angle and the side length of an observed value in a robot network adjustment model, establishing a functional relation between the observed value and a coordinate parameter of a selected unknown point, and then linearizing the observed value, wherein the linearized observed value is in a form shown in a formula (1) and a formula (2), and if two end points of the side length or three end points corresponding to the angle contain known points, corresponding parameters in a side length error equation or an angle error equation do not exist;
observation side length error equation:
observation angle error equation:
setting n observation values and t unknown points in the whole network, wherein the total error equation is as follows:
under the least squares method, the normal equation can be obtained:
BTPBx＝BTPL。
in the above technical solution, in step six, the composition and solution of the normal equation (the composition and solution of the normal equation are prior art);
according to the characteristics of indirect adjustment, after traversing all observed values, obtaining a normal equation coefficient matrix B through matrix basic operationTPB and constant term matrix BTPL, according to the observed value, determining the non-zero element values in the error equation coefficient matrix B and the constant term matrix L, wherein the generation algorithm of the error equation coefficient matrix B and the constant term matrix L is as follows (as shown in FIG. 2):
step S21: starting construction;
step S22: taking out the side length observation values i2 one by one, and taking out the coordinates of the two end points from the coordinate array according to the numbers of the two end points;
step S23: according to the characteristics of the error equation after linearization, calculating coefficients before parameters, and assigning the coefficients to corresponding position elements of the i1 th row in an error equation coefficient matrix B and a constant term matrix L, namely B (i1, 2j-1), B (i1, 2j), B (i1, 2k-1), B (i1, 2k) and L (i1, 1), wherein if one point of two end points of the side length is a known point, the corresponding position element in the B matrix is zero;
determining whether the side length observation value is taken completely; when the side length observation value is not completely obtained, jumping to the step S22;
when the side length observation value is completely obtained, jumping to the step S24;
step S24: taking out the angle observation values i2 one by one, wherein the angle corresponds to 3 endpoint point numbers, namely a station j, a front viewpoint h and a rear viewpoint k, and taking out the point coordinates of 3 points from the coordinate array;
step S25: according to the characteristics of an angle error equation after linearization, coefficients before parameter calculation are respectively assigned to position elements corresponding to the i1+ i2 th row in an error equation coefficient matrix B and a constant term matrix L, namely B (i1+ i2, 2j-1), B (i1+ i2, 2j), B (i1+ i2, 2k-1), B (i1+ i2, 2k), B (i1+ i2, 2h-1), B (i1+ i2, 2h) and L (i1+ i2, 1), if three points corresponding to the angle contain known points, the corresponding position elements in the row of the B matrix are zero;
confirming whether the angle observation value is completely taken; when the angle observation value is not completely obtained, jumping to step S24;
when the angle observation value is completely obtained, jumping to step S26;
step S26: the total error equation coefficient matrix B and the constant term matrix L are constructed;
step S27: finishing construction;
the coefficient term B and the constant term l of the error equation are obtained by the calculation, and the coefficient term N of the normal equation is formedBBConstant term BTPl。
By
Calculating parameter correction number
In the above technical solution, in the sixth step, the method for calculating the coordinate values of the monitoring points is as follows (the method for calculating the coordinate values of the monitoring points is the prior art):
step S31: coordinate mean square difference value
Calculating (1);
correcting the coordinates by a number
Adding the approximate coordinate value to obtain the coordinate adjustment value
Step S32: average value of observed value
Calculating (1);
adding the correction of each observation value to each side length and angle observation value to obtain an observation value adjustment value
In the above technical solution, the precision calculation method is as follows (the precision calculation method is the prior art):
step S41: error in unit weight;
step S42: error in the point location of the undetermined point;
by
Weighted reciprocal of unknown number
Then
The real-time networking automatic adjustment calculation method of the measuring robot has the following advantages:
1) the result is reliable; the invention provides a method for automatically calculating the deformation monitoring of a measuring robot by directly utilizing a corner control net, and the implementation effect analysis shows that the calculation method is rigorous in theory and reliable in result.
2) The precision is improved; the real-time networking automatic adjustment calculation method for the measuring robot can acquire the corrected meteorological factors in real time, solves the problem that a single measuring robot polar coordinate measuring method is limited by the visibility condition and the maximum target identification distance, and can realize real-time networking calculation of the dynamic positions of a plurality of measuring robot stations and monitoring points, thereby acquiring the real-time motion track of the high-precision monitoring points and having good social benefit and economic benefit.
The invention has high monitoring precision and fast monitoring speed, and meets various visual conditions and deformation monitoring of deformation bodies in various deformation areas. The invention calculates the real-time networking of the dynamic positions of a plurality of measuring robot stations and monitoring points (including a real-time meteorological correction model), thereby obtaining the real-time motion trail of the monitoring points with high precision (the stability and the precision of the real-time networking adjustment calculation result of the measuring robot are obviously superior to those of the measuring robot based on a polar coordinate measuring method); the method overcomes the defects that the automatic monitoring of a single measuring robot in the prior art only adopts a polar coordinate method, and the precision is limited by the through-viewing condition and the maximum target identification distance.
Drawings
FIG. 1 is a flow chart of an automatic corner network approximate coordinate approximation algorithm in the present invention.
FIG. 2 is a flow chart of an algorithm for generating an error equation coefficient matrix and a constant term matrix according to the present invention.
Fig. 3 is a layout diagram of a control network of a hydraulic junction project according to an embodiment of the present invention.
FIG. 4 is a process flow diagram of the present invention.
Fig. 5 is a control flow chart of the autonomous research and development observation software system for controlling the measurement robot at the smart site according to the present invention.
FIG. 6 is a schematic circuit diagram of the present invention.
FIG. 7 is a diagram illustrating the software contents of the present invention.
Fig. 8 is a schematic structural diagram of an embodiment of the present invention.
Fig. 9 is a bottom view of fig. 8.
In the figure, 1-a temperature sensor, 2-a humidity sensor, 3-an air pressure sensor, 4-a single chip microcomputer, 5-a crystal oscillator circuit, 6-a battery, 7-a linear voltage stabilizer, 8-a Bluetooth template, 9-a power line, 10-a signal line, 11-a single chip microcomputer initialization module, 12-SHT30-IIC communication protocol module, 13-an analog-digital conversion acquisition module, 14-SPI communication protocol module, 15-MODBUS protocol module, 16-a program operation frame, A-a main control circuit board, B-a sensor component, C-single chip microcomputer built-in software, D-integrated radiation protection cover, D1-a first layer structure, D2-a second layer structure, D3-a third layer structure, D4-a fourth layer structure and D5-a fifth layer structure.
Detailed Description
The embodiments of the present invention will be described in detail with reference to the accompanying drawings, which are not intended to limit the present invention, but are merely exemplary. While the advantages of the invention will be clear and readily understood by the description.
The invention provides a method for carrying out real-time networking adjustment calculation on measuring robots, arranging sensors in a measuring area to automatically acquire real-time meteorological factors, and correcting the meteorological factors through a space interpolation and difference method, thereby realizing remote intelligent control on a plurality of measuring robots, and enabling stations of the measuring robots to be mutually matched and coordinate networking operation. The automatic measurement unattended operation is realized, and the intelligent judgment and processing functions on target shielding are realized. The real-time networking calculation (including a real-time meteorological correction model) of the dynamic positions of the plurality of measuring robot stations and the monitoring points is realized, so that the real-time motion track of the high-precision monitoring points is obtained. Compared with a common polar coordinate measuring method, the real-time networking adjustment method corrects meteorological factors of a measuring area, the adjustment result is less influenced by the observation gross error of a single measuring station, and the three-dimensional coordinates of the monitoring point obtained through calculation are more reliable. The stability and the precision of the real-time networking adjustment calculation result of the measuring robot are obviously superior to those of a polar coordinate-based measuring method.
The dynamic networking monitoring is realized through the whole steps sequentially executed, and the monitoring precision is high and quick; the defects that only static single-point monitoring is adopted, the monitoring precision is low and the monitoring speed is low in the prior art are overcome.
The principle of the invention is as follows:
in the deformation monitoring of the measuring robot, environmental factors such as temperature, atmospheric refraction, air pressure and air disturbance can cause micro-motion changes of a reference point, a monitoring point and a measuring station, so that deviation of a measured angle and a measured distance is caused. Under the condition that the observation area is not large, the meteorological environment is considered to be relatively stable in a short period, so that the spatial interpolation method can interpolate meteorological elements of other monitoring points through a meteorological station, and the calculation method is shown as the following formula:
wherein Z is the meteorological interpolation, ZiIs the ith (i ═ 1.., n), DiIs the distance, p is the power of the distance, which significantly affects the interpolation result, and the selection criterion is the minimum mean absolute error
Since the ranging is subject to refraction and thus to slight deviations due to air temperature and pressure, the effect of changes in atmospheric conditions on the distance measurement must be taken into account in the automatic monitoring process. Generally, each datum point is stable, and the meteorological conditions, the directions and the observation sequences of the positions of the datum point and the monitoring point are consistent in a small range. The slope distance of the monitoring point is corrected by using the slope distance change generated between the fixed reference point and the station-measuring point in different periods, so that the meteorological parameters do not need to be acquired again.
Selecting n reference points, wherein the number of the general reference points is more than 2, the reference points and the initial coordinates of the station are known, and obtaining the actual distance S' from the station to the reference points according to the European formulaO1(initial value). Setting the distance measured between the jth periodic measurement station O and the nth reference point as S ″OjThe slope measured in the j-th cycle and the 1 st cycle are deviated from each other by the same reference point, and the difference is considered to be caused by the meteorological change, so that the meteorological error proportionality coefficient can be obtained as follows:
in order to make the meteorological error proportionality coefficient more accurate, the meteorological error proportionality coefficient of each reference point is summed to obtain a median value to obtain an average error coefficient to correct the side length of the monitoring point, so that the problems of overlarge offset and instrument self-failure caused by different meteorological conditions of a single reference point can be solved. If the jth cycle monitoring point is measuredThe side length of M is S'MThen, the side length after the distance difference correction is:
sM＝S″M-ΔS·S′M
similarly, considering the influence of meteorological conditions on the angle, selecting n reference points, and solving the actual angle from the station to the reference points
(initial value). Let the angle measured between the jth periodic measurement station O and the nth reference point be
The expression of the angle correction number is obtained as follows:
if the angle of the monitored point M of the j period is measured to be alpha'MThe weather-corrected angle is as follows:
αM＝α′M+Δα
examples
The invention will now be described in detail by taking an example of the invention intended for a hydro-junction control network, and has a guiding effect on the application of the invention to other surveying and mapping control networks.
A hydro-hub control network (as shown in fig. 3) is composed of 46 points, wherein the points 203, 204, 205, 206 and 207 are 5 stations, the points 1-41 are 41 monitoring points, and the control area is about 2km2. And (4) constructing observation piers with forced centering bases at all the observation stations and the monitoring points.
In this embodiment, the autonomous research and development observation software system is adopted to control the measurement robot on the intelligent measurement station to automatically find the reference point and the target of the monitoring point, perform clockwise observation, and obtain the real-time angle and distance observation value (which is the real-time meteorological correction factor) so as to meet various visual conditions and deformation monitoring of deformation bodies in various deformation areas, expand the monitoring range, improve the deformation monitoring precision, and improve the monitoring efficiency and speed.
In this embodiment, the real-time weather correction factor is obtained, and the weather station interpolation and weather difference correction are applied to the real-time weather correction of the distance observation value of the measurement robot, so as to improve the distance measurement accuracy.
In this embodiment, the error in the point location of the monitoring point is calculated, and the error in the point location is used for evaluating the coordinate precision of the monitoring point calculated in the sixth step, so as to improve the automatic deformation monitoring precision of the measuring robot.
In the embodiment, intelligent measuring instruments (namely meteorological sensors) for temperature, humidity and air pressure are uniformly arranged at the distributed meteorological acquisition points and are used for acquiring meteorological factors for temperature, humidity and air pressure in real time; the temperature, humidity and air pressure intelligent measuring instrument is an atmospheric temperature, humidity and air pressure intelligent measuring instrument. The intelligent atmosphere temperature and humidity pressure measuring instrument comprises a main control circuit board A, a sensor component B and a singlechip built-in software C; an integrated radiation shield D is arranged on the periphery of the main control circuit board A and the sensor component B;
the integrated radiation shield D in the embodiment is in a shutter shape; the integrated radiation shield D in the embodiment comprises a first layer structure D1, a second layer structure D2, a third layer structure D3, a fourth layer structure D4 and a fifth layer structure D5; the first layer structure D1, the second layer structure D2, the third layer structure D3, the fourth layer structure D4 and the fifth layer structure D5 are sequentially arranged from top to bottom; the main control circuit board A is arranged on the first layer structure D1; the sensor component B is disposed on the fourth layer structure D4; the thermal insulation members are respectively disposed on the second layer structure D2, the third layer structure D3 and the fifth layer structure D5. Thermal insulation components are known in the art.
The sensor component B is simultaneously integrated with three sensors, namely a temperature sensor 1, a humidity sensor 2 and an air pressure sensor 3; the temperature sensor 1 and the humidity sensor 2 are integrated sensors of SHT20 type temperature and humidity of SENSITION company, the temperature range is-40 ℃ to +80 ℃, the resolution is 0.01 ℃, the precision is +/-0.5 ℃, the humidity range is 0% to 100%, the resolution is 0.01%, the precision is +/-3%, and the data interface is I2C; the air pressure sensor 3 is an MS5540C type air pressure sensor produced by INTERSEMA company, the measuring range of the air pressure sensor is 600hPa to 1100hPa, the resolution is 0.1hPa, the precision is +/-0.1% FS, and the data output mode is an SPI interface.
The main control circuit board A includes: battery 6, linear voltage regulator 7, crystal oscillator circuit 5, singlechip 4, bluetooth module 8. The capacity of the battery 6 is 420mAh, and the battery can be charged, can work for 38 hours after being fully charged and is compatible with a mobile phone charger; the linear voltage regulator 7 is an HT7133 type linear voltage regulator produced by HOLTEK company, and the output voltage is 3.3V; the frequency of the crystal oscillator 5 is as follows: 7.3728MHZ, the working temperature range is: -50 ℃ to 85 ℃; the singlechip 4 is an ATMEGA8 type singlechip manufactured by atmel company; the model of the Bluetooth module 8 is HC-05.
The battery 6 is connected with the linear voltage stabilizer 7 through a power line 9; the battery 6 is respectively connected with the sensor component B, the singlechip 4 and the Bluetooth module 8 through the linear voltage stabilizer 7 and the power line 9. The crystal oscillator circuit 5 is connected with the singlechip 4 through a signal wire 10; the Bluetooth module 8 is connected with the singlechip 4 through a signal wire 10. The single chip microcomputer 4 is connected with the sensor component B through a signal line 10 (namely, the single chip microcomputer 4 is respectively connected with the temperature sensor 1, the humidity sensor 2 and the air pressure sensor 3 through the signal line 10).
The singlechip 4 is provided with singlechip built-in software C; the single chip microcomputer built-in software C comprises: the single chip microcomputer initialization module 11 is used for initializing various parameters required by the normal operation of the single chip microcomputer; the SHT30-IIC communication protocol module 12 is used for collecting temperature and humidity data; the analog-to-digital conversion acquisition module 13 is used for correcting the sensor; the SPI communication protocol module 14 is used for collecting air pressure data; the MODBUS protocol module 15 is used for uploading acquired sensor data and configuring sensor parameters; and the program operation framework 16 ensures the stable and ordered operation of the program. The program language used by the protocol module is C language, ICC AVR7 is used for integrating development environment editing, compiling, and the file obtained by compiling is stored in the singlechip and is executed by the singlechip.
In the embodiment, the calculation accuracy comparison results of each monitoring point by using the traditional polar coordinate method and the meteorological factor acquisition and difference correction technology of the invention and adopting the real-time networking adjustment method are shown in table 1, and the comparison results of the calculation accuracies of different meteorological correction methods are shown in table 2.
TABLE 1 comparison of calculation accuracy between polar coordinate method and net-building adjustment method
TABLE 2 comparison of calculation accuracy for different weather correction methods
And (4) conclusion: through the calculation result of the certain hydro junction control network in the embodiment, the accuracy of the real-time networking adjustment calculation result of the measuring robot meets the standard requirement and is high; compared with the traditional meteorological correction method, the real-time difference correction method and the spatial interpolation meteorological correction method can effectively improve the calculation precision and have better application value.
Other parts not described belong to the prior art.
Claims (6)
1. A real-time networking automatic adjustment calculation method for a measurement robot is characterized by comprising the following steps: comprises the following steps of (a) carrying out,
the method comprises the following steps: establishing an intelligent measuring station, establishing a reference point and establishing a monitoring point;
establishing an intelligent testing station: establishing a plurality of intelligent test stations on a stable foundation according to the test area condition to form an intersection network, wherein each set of intelligent test station is provided with a set of automatic observation systems of a measuring robot;
establishing a reference point: uniformly establishing stable reference points according to the conditions of the measurement areas, wherein a set of single prism group which is over against the intelligent measurement station is arranged on the established reference points, forced centering devices of the prisms are embedded into a concrete observation pier, and the direction and the distance from the intelligent measurement station to each reference point cover the whole measurement area;
establishing a monitoring point: monitoring points are uniformly distributed on a monitoring object deformation body according to the section, one or more sets of single prism groups or 360-degree prism groups facing the intelligent measuring station are arranged on the established monitoring points, and forced centering devices of the prisms are embedded in the concrete observation pier;
step two: laying meteorological acquisition points and acquiring meteorological data;
arranging meteorological acquisition points on the intelligent measuring station and the reference point, and arranging meteorological acquisition points on representative monitoring points arranged on the deformation body according to the cross section;
the distributed meteorological acquisition points are uniformly provided with independently developed intelligent measuring instruments for atmospheric temperature, humidity and pressure, and the intelligent measuring instruments are used for acquiring meteorological factors of temperature, humidity and pressure in real time;
step three: acquiring angles and distances in real time;
an autonomous research and development observation software system controls a measurement robot on an intelligent measurement station to automatically search for a reference point and a monitoring point target, clockwise observation is carried out, and a real-time angle and distance observation value is obtained;
step four: performing real-time meteorological correction;
acquiring real-time meteorological correction factors, and performing real-time meteorological correction on the distance observed value of the measuring robot;
the real-time meteorological correction method comprises a meteorological space interpolation method and a meteorological aberration correction method;
the meteorological space interpolation method comprises the steps of utilizing an intelligent temperature, humidity and air pressure measuring instrument to obtain corrected meteorological factors in real time, establishing a temperature, humidity and air pressure meteorological model of a measuring area, interpolating meteorological values at monitoring points of non-laid meteorological acquisition points, and correcting the meteorological factors of observed values of distances from an intelligent measuring station to the monitoring points;
the meteorological difference correction method comprises the following steps: correcting the distance observation value between the intelligent survey station and the monitoring point by using the change values generated between the intelligent survey station and the reference point in different periods as meteorological factor influence values;
step five: calculating approximate coordinates of monitoring points, determining the weights of observation angles and distances, and establishing an angle and distance error equation;
calculating approximate coordinates of monitoring points: calculating approximate coordinates of the monitoring points by using the geometric relation between the real-time observation values;
determine weights for observation angle and distance: determining the weights of the observation angle and the distance according to the precision of the observation angle and the distance;
establishing an angle and distance error equation: determining an angle and distance error equation according to the established geometric relationship between the observed values;
step six: composition and solution of a normal equation;
establishing a method equation and resolving the method equation according to a least square method by using the established error equation to obtain two-dimensional coordinates of each monitoring point;
step seven: calculating errors in the point positions of the monitoring points;
calculating errors in the point positions of the monitoring points, wherein the errors in the point positions are used for evaluating the coordinate precision of the monitoring points calculated in the sixth step;
step eight: and repeating the step two meteorological data acquisition and the step seven monitoring point position error calculation to acquire the monitoring point coordinates of the second period.
2. The method for calculating the automatic adjustment of the real-time networking of the measuring robot according to claim 1, wherein: in step three, the specific control method of the autonomous research and development observation software system for controlling the measurement robot on the intelligent measurement station is as follows:
s31: starting control of the measuring robot;
s32: setting an observation precision grade, an observation return number and a limit difference value, and selecting a zero direction point;
s33: setting a meteorological acquisition interval and starting to acquire meteorological data;
s34: controlling the measuring robot to observe the horizontal angle clockwise;
s35: determining whether the horizontal angle of step S34 is out of limit;
when the horizontal angle exceeds the limit, jumping to step S34;
when the horizontal angle does not exceed the limit, jumping to step S36;
s36: controlling the measuring robot to observe the side length and the vertical angle clockwise;
s37: determining whether the side length and the vertical angle in S36 are out of limit;
when the side length and the vertical angle are out of limit, jumping to step S36;
and finishing the control when the side length and the vertical angle do not exceed the limit.
3. The method for calculating the automatic adjustment of the real-time networking of the measuring robot according to claim 2, wherein: the independently developed intelligent measuring instrument for the atmospheric temperature, humidity and pressure comprises a main control circuit board (A) and a sensor component (B); an integrated radiation shield (D) is arranged on the periphery of the main control circuit board (A) and the sensor component (B);
the master control circuit board (A) comprises a singlechip (4), a crystal oscillator circuit (5), a battery (6), a linear voltage stabilizer (7) and a Bluetooth template (8);
a temperature sensor (1), a humidity sensor (2) and an air pressure sensor (3) are integrated on the sensor component (B);
the battery (6) is connected with the linear voltage stabilizer (7);
the linear voltage stabilizer (7) is respectively connected with the temperature sensor (1), the humidity sensor (2), the air pressure sensor (3), the singlechip (4) and the Bluetooth template (8);
the Bluetooth template (8) is connected with the singlechip (4);
the crystal oscillator circuit (5) is connected with the singlechip (4);
the single chip microcomputer (4) is respectively connected with the temperature sensor (1), the humidity sensor (2) and the air pressure sensor (3).
4. The method for calculating the automatic adjustment of the real-time networking of the measuring robot according to claim 3, wherein: the singlechip (4) is provided with singlechip built-in software (C);
the single chip microcomputer built-in software (C) comprises a single chip microcomputer initialization module (11), an SHT30-IIC communication protocol module (12), an analog-to-digital conversion acquisition module (13), an SPI communication protocol module (14) and an MODBUS protocol module (15);
the single chip microcomputer initialization module (11), the SHT30-IIC communication protocol module (12), the analog-to-digital conversion acquisition module (13), the SPI communication protocol module (14) and the MODBUS protocol module (15) are sequentially connected;
the MODBUS protocol module (15) is connected to the SHT30-IIC communication protocol module (12) through a program operation framework (16).
5. The method for calculating the automatic adjustment of the real-time networking of the measuring robot according to claim 4, wherein: an I2C interface is arranged on the singlechip (4);
I2C interfaces are arranged on the temperature sensor (1) and the humidity sensor (2);
an I2C interface of the singlechip (4) is connected with I2C interfaces of the temperature sensor (1) and the humidity sensor (2);
the single chip microcomputer (4) is provided with an SPI interface; an SPI interface is arranged on the air pressure sensor (3); the single chip microcomputer (4) is communicated with the air pressure sensor through an SPI communication protocol module; the SPI interface of singlechip (4) and the SPI interface of baroceptor (3) are connected.
6. The method for calculating the automatic adjustment of the real-time networking of the measuring robot according to claim 5, wherein: the single chip microcomputer (4) is provided with a UART interface;
a UART interface is arranged on the Bluetooth template (8); the UART interface of the singlechip (4) is connected with the UART interface of the Bluetooth module (8);
the Bluetooth module (8) transmits data to an upper computer;
the singlechip (4) is communicated with an upper computer through an MODBUS protocol module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111163239.7A CN113916260B (en) | 2021-09-30 | 2021-09-30 | Real-time networking automatic adjustment calculation method for measuring robot |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111163239.7A CN113916260B (en) | 2021-09-30 | 2021-09-30 | Real-time networking automatic adjustment calculation method for measuring robot |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113916260A true CN113916260A (en) | 2022-01-11 |
| CN113916260B CN113916260B (en) | 2023-05-16 |
Family
ID=79237686
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111163239.7A Active CN113916260B (en) | 2021-09-30 | 2021-09-30 | Real-time networking automatic adjustment calculation method for measuring robot |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113916260B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120065902A1 (en) * | 2010-09-14 | 2012-03-15 | Canon Kabushiki Kaisha | Sensor apparatus and robot apparatus |
| CN106599483A (en) * | 2016-12-16 | 2017-04-26 | 鞍钢集团矿业有限公司 | Processing method of open-pit mine slope monitoring plane data based on measurement robot |
| CN107449393A (en) * | 2017-09-18 | 2017-12-08 | 机械工业勘察设计研究院有限公司 | A kind of urban track traffic tunnel deformation monitoring system and method |
| CN107631718A (en) * | 2017-08-31 | 2018-01-26 | 山东大学 | A kind of intelligent robot monitoring system and method based on TM30 |
| CN110906902A (en) * | 2019-12-05 | 2020-03-24 | 国电大渡河流域水电开发有限公司 | Two-step correction method for slope deformation monitoring data |
-
2021
- 2021-09-30 CN CN202111163239.7A patent/CN113916260B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120065902A1 (en) * | 2010-09-14 | 2012-03-15 | Canon Kabushiki Kaisha | Sensor apparatus and robot apparatus |
| CN106599483A (en) * | 2016-12-16 | 2017-04-26 | 鞍钢集团矿业有限公司 | Processing method of open-pit mine slope monitoring plane data based on measurement robot |
| CN107631718A (en) * | 2017-08-31 | 2018-01-26 | 山东大学 | A kind of intelligent robot monitoring system and method based on TM30 |
| CN107449393A (en) * | 2017-09-18 | 2017-12-08 | 机械工业勘察设计研究院有限公司 | A kind of urban track traffic tunnel deformation monitoring system and method |
| CN110906902A (en) * | 2019-12-05 | 2020-03-24 | 国电大渡河流域水电开发有限公司 | Two-step correction method for slope deformation monitoring data |
Non-Patent Citations (4)
| Title |
|---|
| 何荣，崔灿: "基于间接平差的自由设站点与监测点 联合平差研究", 河南理工大学学报( 自然科学版) * |
| 张勇: "基于高精度测量机器人的位移监测应用分析", 城市勘测 * |
| 张辛，杨爱明，姜本海: "滇中引水工程测量控制系统的研究与实践", 人民长江 * |
| 李建川，张宇，史波: "高边坡变形监测电磁波测距边长气象改正方法", 人民长江 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113916260B (en) | 2023-05-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108181636B (en) | Environment modeling and map building device and method for petrochemical plant inspection robot | |
| CN107734457B (en) | Intelligent parking lot navigation system and method | |
| CN103472823B (en) | A kind of grating map creating method of intelligent robot | |
| CN101413806B (en) | Mobile robot grating map creating method of real-time data fusion | |
| CN111536967A (en) | EKF-based multi-sensor fusion greenhouse inspection robot tracking method | |
| CN103984981B (en) | Building environmental sensor measuring point optimization method based on Gaussian process model | |
| CN102072747B (en) | Thermal parameter field monitoring-based building group energy consumption monitoring system and method thereof | |
| CN103645490A (en) | Method for monitoring attitude of continuous operating reference station (CORS) of global navigation satellite system (GNSS) | |
| CN113124880B (en) | Map building and positioning method and device based on two sensor data fusion | |
| CN106595608B (en) | The general surveying instrument of distributed interactive | |
| Zhou et al. | Accuracy analysis of dam deformation monitoring and correction of refraction with robotic total station | |
| CN113532397A (en) | Regional elevation anomaly fitting method based on extension algorithm | |
| CN108151698A (en) | A kind of antenna rotation center Calibration Method for intersecting method based on axis | |
| CN109299547A (en) | It is a kind of suitable for whole star and the analysis method of the in-orbit thermal deformation of equipment | |
| CN111811400A (en) | Combined positioning device and method based on AGV and laser tracker | |
| CN106671081B (en) | A kind of lower-mobility robot kinematics calibration method based on monocular vision | |
| CN113916260A (en) | Automatic adjustment calculation method for real-time networking of measuring robot | |
| CN116045935B (en) | Method and device for measuring relative azimuth and attitude of adjacent joint space | |
| CN111928851A (en) | Multi-autonomous underwater robot cluster collaborative navigation method based on TMA technology | |
| CN117359613A (en) | Robot error compensation method based on self-adaptive Kalman filtering and neural network | |
| CN115675784B (en) | Ship block docking system and docking method based on digital measuring field | |
| CN114740798B (en) | Method for constructing measuring field of numerical control equipment group cooperative production line | |
| CN114894167B (en) | Automatic cave mapping system and method based on multi-sensor technology | |
| CN111121818A (en) | Calibration method for camera and two-dimensional code in unmanned vehicle | |
| CN115507827A (en) | Net-shaped distributed landslide monitoring system based on ultra wide band and high-precision MEMS (micro-electromechanical systems) |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |