CN107797094A - A kind of mobile robot position and orientation estimation method based on RFID - Google Patents
A kind of mobile robot position and orientation estimation method based on RFID Download PDFInfo
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- CN107797094A CN107797094A CN201711104939.2A CN201711104939A CN107797094A CN 107797094 A CN107797094 A CN 107797094A CN 201711104939 A CN201711104939 A CN 201711104939A CN 107797094 A CN107797094 A CN 107797094A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/0247—Determining attitude
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Abstract
The invention discloses a kind of mobile robot position and orientation estimation method based on RFID, mainly include：Step 100：Robot location's coordinate algorithm for estimating based on RFID reception wireless signal strength；Step 200：The estimation of mobile robot azimuth angle theta.A kind of mobile robot position and orientation estimation method based on RFID of the present invention, robot positioning system based on RFID signal intensity is combined with the robot localization algorithm based on Maximum-likelihood estimation, and weighted least square algorithm is applied in the maximum likelihood equations group solution of robot coordinate, realize the fusion of two kinds of algorithms, it is effectively improved positioning precision, and system is protected from environmental small, position error is more stable.
Description
Technical field
The present invention relates to based on RFID localization for Mobile Robot technical fields, in particular it relates to a kind of shifting based on RFID
Mobile robot position and orientation estimation method.
Background technology
With the development that robot applies in people's daily life, the research of indoor moving service robot turns into focus.
Indoors in intelligent robot location modeling, self poisoning and the pose estimated capacity of robot for path planning and are transported
Dynamic control is of crucial importance, is the key that robot realizes independent navigation, and the automatization level for improving robot has important
Meaning.At present, GPS is widely used in mobile robot positioning system, but due to by Costco Wholesale, power consumption,
The influence of the factors such as scalability, in face of the indoor environment of complexity, easily produce and position larger error, it is impossible to which target is carried out
Real-time tracking positions.
The pose measurement system of view-based access control model, by the use of vehicle mounted camera shooting to surrounding environment in certain objects as
Reference point, the autonomous positioning and pose for realizing mobile robot are estimated, but the method is easily influenceed by external environment conditions such as illumination.
Laser range sensor and ultrasonic distance-measuring sensor system are by the distance between robot and surrounding objects, there is provided accurate
Positional information position, but it is vulnerable to the influence of multipath effect and non line of sight effect, position error be present is one impassable
Obstacle.
According to receiving wireless signal strength to position be the focus location technology studied now.Positioning based on signal intensity
Method is without additional hardware, and detection device and mechanism are simple, and hardware cost is low, easily realize, using to receiving wireless signal
Intensity, the distance between transmitting-receiving node is calculated, thus wireless sensor network positions the location technology based on signal intensity indoors
It is more conventional in technology.
Video identification technology (RFID) is a kind of non-contact sensor technology, because it has traditional sensor technology institute
The advantages of not possessing and the concern for increasingly causing people.RFID technique is not influenceed by light intensity, not by dense smoke, thick fog,
The influence of dust, therefore be widely used in the indoor environment of factory, colliery and complexity.
Therefore, the present invention proposes a kind of position of mobile robot positioning based on RFID signal intensity and pose estimation side
Method, the robot positioning system based on RFID signal intensity and the robot localization algorithm based on Maximum-likelihood estimation are mutually tied
Close, and weighted least square algorithm is applied in the maximum likelihood equations group solution of robot coordinate, realize two kinds of algorithms
Fusion, be effectively improved positioning precision, and system is protected from environmental small, position error is more stable.
The content of the invention
It is an object of the present invention in view of the above-mentioned problems, propose a kind of mobile robot pose estimation side based on RFID
Method, positioning precision is effectively improved to realize, the advantages of system is protected from environmental small and position error is stable.
To achieve the above object, the technical solution adopted by the present invention is：A kind of mobile robot pose based on RFID is estimated
Meter method, mainly includes：
Step 100：Position coordinates algorithm for estimating based on RFID reception wireless signal strength；
Step 200：The estimation of mobile robot azimuth angle theta.
Further, the step 100 specifically includes：
Step 110：The Maximum Likelihood Estimation Method model of robot coordinate is established by adaptive Maximum Likelihood Estimation；
Step 120：Maximum likelihood equations group is solved with weighted least-squares method.
Further, the step 110 specifically includes：
Step 111：Using log normal propagation of distributions model, the distance d for obtaining outgoing label to read write line receives with read write line
Functional relation between the signal strength values P (d) of the label arrived；
Step 112：According to the normal distyribution function of signal strength values, the signal intensity of reference label is obtained；
Step 113：Using adaptive Maximum Likelihood Estimation Method calculation position coordinate.
Further, the step 111 specifically includes：
Using radio signal propagation principle, in the ideal situation, using log normal propagation of distributions model, it can be deduced that mark
The functional relation registered between the signal strength values P (d) of label that the distance d of read write line and read write line receive is：
In formula, n is signal propagation constant, p (d0) it is to signal strength values during d=1m；In certain environment, p (d0) with
N value is all known, so just can be derived that d value by measuring p (d) values.
Further, the step 112 specifically includes：
According to statistical theory, the signal strength values under some distance meet normal distribution, and probable value is bigger, illustrate to survey
The signal strength values of amount and actual value are closer.Therefore priority treatment is carried out to the signal strength values read.Normal distribution is close
Spending function is
Maximum likelihood function is
Wherein, μ, δ2It is the average and standard deviation repeatedly measured.If it is m, μ and δ to measure number2Maximum likelihood estimate
Evaluation is
Wherein, xiFor the signal strength values of i-th of RFID label tag.Bring the signal strength values of actual measurement into formula (4), obtain μ
And δ2, then bring formula (3) into, obtain L (μ, δ) value, retain the measured value that L (μ, δ) value is 0.5~1, it is averaging, make
The signal intensity of the reference label read for robot.
Further, the step 113 specifically includes：
a：Vehicle-mounted RFID reader is in robot kinematics, according to the RFID on the wireless signal searches ground of reception
Label；
b：The number for the RFID label tag that robot is read every time is adaptive change, according to RFID label tag health status with
RFID signal intensity threshold chooses the number of different RFID label tags；
c：According to the abnormal RFID label tag of wireless signal strength value Weeding received, and it is strong to exclude wireless signal
The relatively low RFID label tag of angle value；
d：Without the selection of geometric configuration, according to Maximum Likelihood Estimation Method model, the n RFID marks left are directly utilized
Sign information and carry out maximum likelihood coordinate estimation.
Further, step d is specifically included described in the step 113：
The coordinate of known 1,2,3, L, n node is (x1,y1),(x2,y2),L,(xn,yn), and they arrive unknown node
T distance is respectively d1,d2,L,dn.Assuming that unknown node T coordinate is (x, y), then
Last equation, which is individually subtracted, in an equation in formula (5) to obtain：
Formula (6) is represented by the form of following linear equation：AXT=B, wherein：
X=[x y].
Further, the step 120 specifically includes：
Linear equation AX is sought below with weighted least-squares method (Weighted Least Square)T=B solution is
X=(ATWA)-1ATWB (7)
In general, the selection of weights selects generally according to the precision of each measurement, should ensure that and unknown RFID label tag
The more remote point of node, because of its precise decreasing, the weight shared by it is smaller, and weights are chosen as follows：
In formula, k is the path attenuation factor, di, i=1,2L, n-1 are distance of i-th of RFID label tag to reader.
Further, the step 200 specifically includes：
According to the kinematic geometry model of robot, the coordinate of robot and the deflection of calculating robot are determined；
In the indoor mobile robot position coordinates estimating system based on RFID signal intensity, according to robot in movement
During geometrical model, it is known that, if robot is known in initial position A pose, be expressed as A (x0,y0,θ0), warp
After crossing a sampling period T time, robot reaches B points position, and coordinate (x of the robot in B points can be calculated by formula (7)k,
yk), it is expressed as (x in the pose of B pointsk,yk,θk).Can obtaining robot by the cosine law, the anglec of rotation is in this process
In formula, R is the radius of turn of certain moment k robots, if the speed of robot left and right wheels is v1With v2, by machine
Photoelectric coded disk on people's wheel measures, and the width of robot is that b, R and l calculation formula are
On the estimation of the deflection θ in robot pose, there is following relation：
θk=θ0+φk
(12)。
The advantageous effects of the present invention：
A kind of mobile robot position and orientation estimation method based on RFID of the present invention, mainly includes：Step 100：It is based on
The position coordinates algorithm of RFID reception wireless signal strength；Step 200：The estimation of mobile robot azimuth angle theta.Believed based on RFID
The robot positioning system of number intensity is combined with the robot localization algorithm based on Maximum-likelihood estimation, and will weight a most young waiter in a wineshop or an inn
Multiplication algorithm is applied in the maximum likelihood equations group solution of robot coordinate, is realized the fusion of two kinds of algorithms, is effectively improved
Positioning precision, and system is protected from environmental small, position error is more stable.
Other features and advantages of the present invention will be illustrated in the following description, also, partly becomes from specification
Obtain it is clear that or being understood by implementing the present invention.
Below by drawings and examples, technical scheme is described in further detail.
Brief description of the drawings
Accompanying drawing is used for providing a further understanding of the present invention, and a part for constitution instruction, the reality with the present invention
Apply example to be used to explain the present invention together, be not construed as limiting the invention.In the accompanying drawings：
Fig. 1 is a kind of robot control system knot of the mobile robot position and orientation estimation method based on RFID of the present invention
Structure schematic diagram；
Fig. 2 is that a kind of system experimental device of mobile robot position and orientation estimation method based on RFID of the present invention is illustrated
Figure；
Fig. 3 is that a kind of adaptive pole maximum-likelihood of the mobile robot position and orientation estimation method based on RFID of the present invention is estimated
Meter tagmeme puts Coordinate calculation method flow chart；
Fig. 4 is a kind of Maximum Likelihood Estimation Method mould of the mobile robot position and orientation estimation method based on RFID of the present invention
Type structural representation；
Fig. 5 is that the robot in a kind of motion of the mobile robot position and orientation estimation method based on RFID of the present invention is several
What model schematic.
Embodiment
The preferred embodiments of the present invention are illustrated below in conjunction with accompanying drawing, it will be appreciated that described herein preferred real
Apply example to be merely to illustrate and explain the present invention, be not intended to limit the present invention.
As shown in Fig. 2 before present invention experiment, RFID label tag is fixed, mobile RFID reader is strong every 5cm measurement signals
Angle value, each position measurement is averaged for 20 times, the p (d in formula (1) are drawn by curve matching0)=- 45.63, n=
1.832.In experimentation, robot continuous 20 signal strength values for reading each reference label at planning point.
A kind of mobile robot position and orientation estimation method based on RFID, mainly includes：
Step 100：Position coordinates algorithm for estimating based on RFID reception wireless signal strength；
Step 200：The estimation of mobile robot azimuth angle theta.
The step 100 specifically includes：
Step 110：The Maximum Likelihood Estimation Method model of robot coordinate is established by adaptive Maximum Likelihood Estimation；
Step 120：Maximum likelihood equations group is solved with weighted least-squares method.
The step 110 specifically includes：
Step 111：Using log normal propagation of distributions model, the distance d for obtaining outgoing label to read write line receives with read write line
Functional relation between the signal strength values P (d) of the label arrived；
Step 112：According to the normal distyribution function of signal strength values, the signal intensity of reference label is obtained；
Step 113：Using adaptive Maximum Likelihood Estimation Method calculation position coordinate.
The step 111 specifically includes：
Using radio signal propagation principle, in the ideal situation, using log normal propagation of distributions model, it can be deduced that mark
The functional relation registered between the signal strength values P (d) of label that the distance d of read write line and read write line receive is：
In formula, n is signal propagation constant, p (d0) it is to signal strength values during d=1m；In certain environment, p (d0) with
N value is all known, so just can be derived that d value by measuring p (d) values.
The step 112 specifically includes：
According to statistical theory, the signal strength values under some distance meet normal distribution, and probable value is bigger, illustrate to survey
The signal strength values of amount and actual value are closer.Therefore priority treatment is carried out to the signal strength values read.Normal distribution is close
Spending function is
Maximum likelihood function is
Wherein, μ, δ2It is the average and standard deviation repeatedly measured.If it is m, μ and δ to measure number2Maximum likelihood estimate
Evaluation is
Wherein, xiFor the signal strength values of i-th of RFID label tag.Bring the signal strength values of actual measurement into formula (4), obtain μ
With δ2, then bring formula (3) into, obtain L (μ, δ) value, retain the measured value that L (μ, δ) value is 0.5~1, it is averaging, make
The signal intensity of the reference label read for robot.
As shown in figure 3, the step 113 specifically includes：
a：Vehicle-mounted RFID reader is in robot kinematics, according to the RFID on the wireless signal searches ground of reception
Label；
b：The number for the RFID label tag that robot is read every time is adaptive change, according to RFID label tag health status with
RFID signal intensity threshold chooses the number of different RFID label tags；
c：According to the abnormal RFID label tag of wireless signal strength value Weeding received, and it is strong to exclude wireless signal
The relatively low RFID label tag of angle value；
d：Without the selection of geometric configuration, according to Maximum Likelihood Estimation Method model, the n RFID marks left are directly utilized
Sign information and carry out maximum likelihood coordinate estimation.
Step d is specifically included described in the step 113：
Maximum Likelihood Estimation Method model according to Fig. 4, it is known that the coordinate of 1,2,3, L, n nodes is
(x1,y1),(x2,y2),L,(xn,yn), and they to unknown node T distance be respectively d1,d2,L,dn.Assuming that
Unknown node T coordinate is (x, y), then
Last equation, which is individually subtracted, in an equation in formula (5) to obtain：
Formula (6) is represented by the form of following linear equation：AXT=B, wherein：
X=[x y].
The step 120 specifically includes：
Linear equation AX is sought below with weighted least-squares method (Weighted Least Square)T=B solution is
X=(ATWA)-1ATWB (7)
In general, the selection of weights selects generally according to the precision of each measurement, should ensure that and unknown RFID label tag
The more remote point of node, because of its precise decreasing, the weight shared by it is smaller, and weights are chosen as follows：
In formula, k is the path attenuation factor, di, i=1,2L, n-1 are distance of i-th of RFID label tag to reader.
The step 200 specifically includes：
According to the kinematic geometry model of robot, the coordinate of robot and the deflection of calculating robot are determined；
In the indoor mobile robot position coordinates estimating system based on RFID signal intensity, according to robot in movement
During geometrical model, as shown in Figure 5, if robot is known in initial position A pose, be expressed as A (x0,y0,
θ0), after a sampling period T time, robot reaches B points position, and seat of the robot in B points can be calculated by formula (7)
Mark (xk,yk), it is expressed as (x in the pose of B pointsk,yk,θk).The robot anglec of rotation in this process can be obtained by the cosine law
For
In formula, R is the radius of turn of certain moment k robots, if the speed of robot left and right wheels is v1With v2, by machine
Photoelectric coded disk on people's wheel measures, and the width of robot is that b, R and l calculation formula are
On the estimation of the deflection θ in robot pose, there is following relation：
θk=θ0+φk (12)。
Following beneficial effect can at least be reached：
A kind of mobile robot position and orientation estimation method based on RFID of the present invention, mainly includes：Step 100：It is based on
The position coordinates algorithm of RFID reception wireless signal strength；Step 200：The estimation of mobile robot azimuth angle theta.Believed based on RFID
The robot positioning system of number intensity is combined with the robot localization algorithm based on Maximum-likelihood estimation, and will weight a most young waiter in a wineshop or an inn
Multiplication algorithm is applied in the maximum likelihood equations group solution of robot coordinate, is realized the fusion of two kinds of algorithms, is effectively improved
Positioning precision, and system is protected from environmental small, position error is more stable.
Finally it should be noted that：The preferred embodiments of the present invention are the foregoing is only, are not intended to limit the invention,
Although the present invention is described in detail with reference to the foregoing embodiments, for those skilled in the art, it still may be used
To be modified to the technical scheme described in foregoing embodiments, or equivalent substitution is carried out to which part technical characteristic.
Within the spirit and principles of the invention, any modification, equivalent substitution and improvements made etc., it should be included in the present invention's
Within protection domain.
Claims (9)
1. a kind of mobile robot position and orientation estimation method and system based on RFID, it is characterised in that mainly include：
Step 100：Position coordinates algorithm for estimating based on RFID reception wireless signal strength；
Step 200：The estimation of mobile robot azimuth angle theta.
2. a kind of mobile robot position and orientation estimation method based on RFID according to claim 1, it is characterised in that described
Step 100 specifically includes：
Step 110：The Maximum Likelihood Estimation Method model of robot coordinate is established by adaptive Maximum Likelihood Estimation；
Step 120：Maximum likelihood equations group is solved with weighted least-squares method.
3. a kind of mobile robot position and orientation estimation method based on RFID according to claim 2, it is characterised in that described
Step 110 specifically includes：
Step 111：Using log normal propagation of distributions model, obtain what the distance d of outgoing label to read write line received with read write line
Functional relation between the signal strength values P (d) of label；
Step 112：According to the normal distyribution function of signal strength values, the signal intensity of reference label is obtained；
Step 113：Using adaptive Maximum Likelihood Estimation Method calculation position coordinate.
4. a kind of mobile robot position and orientation estimation method based on RFID according to claim 3, it is characterised in that described
Step 111 specifically includes：
Using radio signal propagation principle, in the ideal situation, using log normal propagation of distributions model, it can be deduced that label arrives
Functional relation between the signal strength values P (d) for the label that the distance d and read write line of read write line are received is：
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According to statistical theory, the signal strength values under some distance meet normal distribution, and probable value is bigger, illustrates measurement
Signal strength values are closer with actual value.Therefore priority treatment is carried out to the signal strength values read.Normal distribution density letter
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The signal intensity for the reference label that people reads.
6. a kind of mobile robot position and orientation estimation method based on RFID according to claim 3, it is characterised in that described
Step 113 specifically includes：
a：Vehicle-mounted RFID reader is marked in robot kinematics according to the RFID on the wireless signal searches ground of reception
Label；
b：The number for the RFID label tag that robot is read every time is adaptive change, according to RFID label tag health status and RFID
Signal strength threshold value chooses the number of different RFID label tags；
c：According to the abnormal RFID label tag of wireless signal strength value Weeding received, and exclude wireless signal strength value
Relatively low RFID label tag；
d：Without the selection of geometric configuration, according to Maximum Likelihood Estimation Method model, the n RFID label tag letter left is directly utilized
Breath carries out maximum likelihood coordinate estimation.
7. a kind of mobile robot position and orientation estimation method based on RFID according to claim 6, it is characterised in that described
Step d described in step 113 specifically includes：
The coordinate of known 1,2,3, L, n node is (x1,y1),(x2,y2),L,(xn,yn), and they are to unknown node T
Distance respectively d1,d2,L,dn.Assuming that unknown node T coordinate is (x, y), then
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</mtd>
</mtr>
<mtr>
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</msub>
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<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>y</mi>
<mi>n</mi>
</msub>
<mo>-</mo>
<mi>y</mi>
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</mrow>
<mn>2</mn>
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<mo>=</mo>
<msub>
<mi>d</mi>
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</msub>
</mrow>
</mtd>
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</mtable>
</mfenced>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>5</mn>
<mo>)</mo>
</mrow>
</mrow>
Last equation, which is individually subtracted, in an equation in formula (5) to obtain：
<mrow>
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<mo>-</mo>
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<mn>1</mn>
</msub>
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<mi>x</mi>
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<mi>y</mi>
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<mi>n</mi>
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</mrow>
</mrow>
Formula (6) is represented by the form of following linear equation：AXT=B, wherein：
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<mrow>
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<mo>,</mo>
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<mrow>
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<mfenced open = "[" close = "]">
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</mrow>
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</mtable>
</mfenced>
<mo>,</mo>
</mrow>
X=[x y].
8. a kind of mobile robot position and orientation estimation method based on RFID according to claim 2, it is characterised in that described
Step 120 specifically includes：
Linear equation AX is sought below with weighted least-squares method (Weighted Least Square)T=B solution is
X=(ATWA)-1ATWB (7)
In general, the selection of weights selects generally according to the precision of each measurement, should ensure that and unknown RFID label tag node
More remote point, because of its precise decreasing, the weight shared by it is smaller, and weights are chosen as follows：
<mrow>
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<mfenced open = "[" close = "]">
<mtable>
<mtr>
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<mrow>
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<mi>d</mi>
<mn>1</mn>
<mrow>
<mi>k</mi>
<mo>+</mo>
<mn>2</mn>
</mrow>
</msubsup>
</mrow>
</mtd>
<mtd>
<mn>0</mn>
</mtd>
<mtd>
<mi>L</mi>
</mtd>
<mtd>
<mn>0</mn>
</mtd>
</mtr>
<mtr>
<mtd>
<mn>0</mn>
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<mtd>
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</mtd>
<mtd>
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</mrow>
</msubsup>
</mrow>
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</mtr>
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<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>8</mn>
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</mrow>
</mrow>
In formula, k is the path attenuation factor, di, i=1,2L, n-1 are distance of i-th of RFID label tag to reader.
9. a kind of mobile robot position and orientation estimation method based on RFID according to claim 1, it is characterised in that described
Step 200 specifically includes：
According to the kinematic geometry model of robot, the coordinate of robot and the deflection of calculating robot are determined；
In the indoor mobile robot position coordinates estimating system based on RFID signal intensity, according to robot in moving process
In geometrical model, it is known that, if robot is known in initial position A pose, be expressed as A (x0,y0,θ0), by one
After individual sampling period T time, robot reaches B points position, and coordinate (x of the robot in B points can be calculated by formula (7)k,yk),
The pose of B points is expressed as (xk,yk,θk).Can obtaining robot by the cosine law, the anglec of rotation is in this process
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<mo>-</mo>
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<msup>
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<mn>2</mn>
</msup>
<mrow>
<mn>2</mn>
<msup>
<mi>R</mi>
<mn>2</mn>
</msup>
</mrow>
</mfrac>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>9</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula, R is the radius of turn of certain moment k robots, if the speed of robot left and right wheels is v1With v2, by robot car
Photoelectric coded disk on wheel measures, and the width of robot is that b, R and l calculation formula are
<mrow>
<mi>R</mi>
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<mfrac>
<mrow>
<mi>b</mi>
<mrow>
<mo>(</mo>
<msub>
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<mn>1</mn>
</msub>
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<msub>
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</msub>
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</mrow>
</mrow>
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<mrow>
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</msub>
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<msub>
<mi>v</mi>
<mn>2</mn>
</msub>
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</mrow>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
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<mn>10</mn>
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</mrow>
</mrow>
<mrow>
<mi>l</mi>
<mo>=</mo>
<msqrt>
<msup>
<mrow>
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<msub>
<mi>x</mi>
<mn>0</mn>
</msub>
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<msub>
<mi>x</mi>
<mi>k</mi>
</msub>
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</mrow>
<mn>2</mn>
</msup>
</msqrt>
<mo>-</mo>
<msqrt>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>y</mi>
<mn>0</mn>
</msub>
<mo>-</mo>
<msub>
<mi>y</mi>
<mi>k</mi>
</msub>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</msqrt>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>11</mn>
<mo>)</mo>
</mrow>
</mrow>
On the estimation of the deflection θ in robot pose, there is following relation：
θk=θ0+φk (12)。
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| CN109959897A (en) * | 2019-04-08 | 2019-07-02 | 南京邮电大学 | A kind of RFID two-dimensional position localization method based on rotable antenna |
| CN110703188A (en) * | 2019-09-10 | 2020-01-17 | 天津大学 | Six-degree-of-freedom attitude estimation system based on RFID |
| CN111060870A (en) * | 2019-12-04 | 2020-04-24 | 南京邮电大学 | RFID positioning method based on antenna rotation |
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| CN111060870B (en) * | 2019-12-04 | 2022-09-27 | 南京邮电大学 | RFID positioning method based on antenna rotation |
| CN111385348A (en) * | 2020-01-08 | 2020-07-07 | 广州番禺职业技术学院 | Cloud brain robot system |
| CN113534117A (en) * | 2021-06-11 | 2021-10-22 | 广州杰赛科技股份有限公司 | Indoor positioning method |
| CN113534117B (en) * | 2021-06-11 | 2024-06-04 | 广州杰赛科技股份有限公司 | Indoor positioning method |
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