CN113137967B - Robot positioning method, device, robot and readable storage medium - Google Patents
Robot positioning method, device, robot and readable storage medium Download PDFInfo
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- G—PHYSICS
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/18—Stabilised platforms, e.g. by gyroscope
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
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- G—PHYSICS
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- 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
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Abstract
The embodiment of the invention discloses a robot positioning method, a device, a robot and a readable storage medium, wherein the robot comprises a communication module, the communication module is used for receiving pulse signals sent by positioning labels, and the method comprises the following steps: estimating the estimated pose of the robot at the current moment based on the inertial data of the robot, determining an angle reliable tag in each positioning tag through an estimated angle corresponding to the estimated pose of the robot at the current moment, and determining the actual pose of the robot at the current moment based on the relative distance and the relative angle corresponding to the angle reliable tag. According to the technical scheme, the high-frequency inertial measurement unit is utilized to acquire inertial data at a high frequency, and the inertial measurement unit is utilized to acquire the inertial data when the robot moves, so that the positioning based on the high-frequency inertial measurement unit and the positioning based on the communication module-tag are fused, and the robot moving quickly can be accurately positioned.
Description
Technical Field
The present invention relates to the field of artificial intelligence, and in particular, to a robot positioning method, a robot positioning device, a robot, and a readable storage medium.
Background
Positioning technology is a key technology for mobile robot navigation. The robot is accurately positioned in real time through the positioning device, so that the navigation system can plan a path according to the accurate positioning of the robot, and further the robot is controlled to finish work.
The existing common robot positioning modes comprise fixed rail positioning, visual positioning based on a virtual rail, mobile robot visual positioning based on deep learning and the like, and the positioning modes have the defects. For example, a fixed rail is positioned, a guide rail of a metal wire or a magnetic nail is required to be paved on the ground, and a robot walks on the guide rail, but the guide rail is not only inconvenient to install, but also has high maintenance cost; based on visual positioning of the virtual track, a guide line is required to be drawn on the ground, or an ink ribbon is required to be paved, or a two-dimensional code navigation belt is required to be paved, however, the virtual track is easily covered by dust or a movable shielding object, so that the robot cannot be positioned accurately; the mobile robot vision positioning method based on deep learning is complex in algorithm and high in calculation difficulty, and is ideal and low in practicability.
Disclosure of Invention
In view of the above, the present application proposes a robot positioning method, apparatus, robot, and readable storage medium.
The application provides a robot positioning method, which comprises the following steps:
acquiring relative distances and relative angles between the robot and each positioning label;
acquiring inertial data of the robot;
estimating the estimated pose of the robot at the current moment according to the inertial data;
determining a predetermined first number of angle reliable labels from the positioning labels according to the comparison result of the estimated angles in the estimated pose and the relative angles;
and determining the actual pose of the robot at the current moment according to the relative distance and the relative angle corresponding to the preset first number of angle reliable labels.
According to the robot positioning method, a first antenna and a second antenna are installed at a preset position of the robot, the first antenna and the second antenna are used for receiving pulse signals sent by each positioning tag, and the relative distance and the relative angle between the robot and each positioning tag are obtained, and the robot positioning method comprises the following steps:
acquiring a first distance between an ith positioning tag and the first antenna, wherein I is less than or equal to I, and I is the total number of the positioning tags;
acquiring a second distance between an ith positioning tag and the second antenna;
Determining an arrival phase difference of a pulse signal sent by an ith positioning tag to the first antenna and the second antenna;
and determining the relative distance and the relative angle between the robot and the ith positioning label according to the first distance, the arrival phase difference and the second distance.
According to the robot positioning method, the inertial data comprise linear acceleration and angular velocity of the robot, and the estimating pose of the robot at the current moment according to the inertial data comprises the following steps:
estimating the displacement variation of the robot from the last moment to the current moment according to the linear acceleration of the last moment in the inertial data;
estimating the angle change quantity of the robot from the last moment to the current moment according to the angular speed at the last moment in the inertial data;
and estimating the estimated pose of the robot at the current moment according to the displacement variation and the angle variation.
The robot positioning method according to the present application, wherein the determining a predetermined first number of angle reliable tags from the positioning tags according to the comparison result of the estimated angle in the estimated pose and each of the relative angles includes:
Calculating the absolute value of the difference between the relative angle corresponding to the ith positioning label and the estimated angle, wherein I is less than or equal to I, and I is the total number of the positioning labels;
judging whether the absolute value is larger than a preset angle threshold value or not;
if the angle threshold value is smaller than or equal to the angle threshold value, the ith positioning label is reliable;
if the angle threshold is larger than the angle threshold, the ith positioning label is unreliable.
According to the robot positioning method, the determining of the actual pose of the robot at the current moment according to the relative distance and the relative angle corresponding to the predetermined first number of angle reliable labels comprises the following steps:
calculating a mean value corresponding to the relative angle and a variance corresponding to the relative angle according to the relative angles corresponding to the preset first number of angle reliable labels;
determining a predetermined second number of distance-reliable labels according to the relative distances corresponding to the predetermined first number of angle-reliable labels;
calculating a mean value corresponding to the relative distance and a variance corresponding to the relative distance according to the relative distance degree corresponding to the preset second number of distance reliable labels;
and inputting the average value corresponding to the relative angle, the average value corresponding to the relative distance, the variance corresponding to the relative angle and the variance corresponding to the relative distance into a preset unscented Kalman filter to obtain the actual pose of the robot at the current moment.
The robot positioning method described in the application, wherein the determining a predetermined second number of distance-reliable labels according to the relative distances corresponding to the predetermined first number of angle-reliable labels includes:
dividing the predetermined first number of angularly reliable tags into K groups, each group comprising at least 3 angularly reliable tags;
determining the position of the robot according to the angle reliable labels of each group;
calculating the mean value corresponding to the K positions and the variance corresponding to the K positions;
if the variance corresponding to the K positions is larger than a preset variance threshold, deleting the position farthest from the average value corresponding to the K positions in the K positions, and recalculating the average value corresponding to the K-1 positions and the variance corresponding to the K-1 positions until the variance corresponding to the residual positions is smaller than or equal to the preset variance threshold, wherein the positioning label corresponding to the residual positions is a distance reliable label;
if the variance corresponding to the K positions is smaller than or equal to a preset variance threshold, the positioning labels corresponding to the K positions are distance reliable labels.
The application proposes a robot positioning device, the robot includes communication module, communication module is used for receiving the pulse signal that each location label sent, the device includes:
The acquisition unit is used for acquiring the relative distance and the relative angle between the robot and each positioning label; the inertial data acquisition module is also used for acquiring inertial data of the robot;
the estimating unit is used for estimating the estimated pose of the robot at the current moment according to the inertial data;
a screening unit, configured to determine a predetermined first number of angle reliable tags from the positioning tags according to comparison results of the estimated angles and the respective relative angles in the estimated pose;
and the positioning unit is used for determining the actual pose of the robot at the current moment according to the relative distance and the relative angle corresponding to the preset first number of angle reliable labels.
The application robot positioner, communication module includes first antenna and second antenna, first antenna with the second antenna is used for receiving the pulse signal that each positioning label sent, acquire relative distance and relative angle between robot and each positioning label, include:
acquiring a first distance between an ith positioning tag and the first antenna, wherein I is less than or equal to I, and I is the total number of the positioning tags;
acquiring a second distance between an ith positioning tag and the second antenna;
Determining an arrival phase difference of a pulse signal sent by an ith positioning tag to the first antenna and the second antenna;
and determining the relative distance and the relative angle between the robot and the ith positioning label according to the first distance, the arrival phase difference and the second distance.
The application provides a robot, which comprises a memory, a processor and a communication module, wherein the memory stores a computer program, the computer program executes the robot positioning method when running on the processor, and the communication module is used for receiving pulse signals sent by each positioning label.
The present application proposes a readable storage medium storing a computer program which, when run on a processor, performs the described robot positioning method.
According to the robot positioning method, the position relationship between the robot and each positioning tag is determined by utilizing carrier communication between the communication module of the robot and each positioning tag, the estimated pose of the robot at the current moment is estimated based on the inertial data of the robot, the angle reliable tag in each positioning tag is determined through the estimated angle of the estimated pose of the robot at the current moment, and the actual pose of the robot at the current moment is determined based on the relative distance and the relative angle corresponding to the angle reliable tag. According to the method, the high-frequency inertial measurement unit (Inertial measurement unit, IMU) is used, the inertial data are acquired by the inertial measurement unit when the robot moves, and the IMU positioning and the communication module-label positioning are fused, so that the fast moving robot can be accurately positioned. Compared with the existing fixed track positioning and virtual track-based visual positioning, the visual positioning method has the advantages that the practicability is higher, the guide rail is not required to be installed, and special personnel are not required to maintain the guide rail and the guide wire; compared with the existing mobile robot vision positioning method based on deep learning, the method has the advantages of being smaller in calculated amount, simple in algorithm and convenient to calculate.
Drawings
In order to more clearly illustrate the technical solutions of the present invention, the drawings that are required for the embodiments will be briefly described, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope of the present invention. Like elements are numbered alike in the various figures.
Fig. 1 shows a schematic flow chart of a robot positioning method proposed in the present application;
FIG. 2 illustrates a schematic diagram of a method of determining relative distance and relative angle between a robot and a positioning tag as set forth in the present application;
FIG. 3 is a schematic diagram showing a principle of determining a relative distance and a relative angle between a robot and a positioning tag according to the present application;
FIG. 4 is a schematic diagram of a method for determining estimated pose of a robot according to the present application;
FIG. 5 is a schematic diagram of a method for determining an angle-reliable tag according to the present application;
FIG. 6 is a schematic diagram showing a process for determining an angle-reliable label according to the present application;
FIG. 7 is a schematic diagram of a method for determining an actual pose of a robot according to the present application;
FIG. 8 illustrates a schematic diagram of a method of determining a distance-reliable tag as set forth herein;
Fig. 9 shows a schematic structural diagram of a robotic positioning device according to the present application;
fig. 10 shows a schematic structural diagram of a robot proposed in the present application.
Description of main reference numerals:
10-a robotic positioning device; 11-an acquisition unit; 12-an estimation unit; 13-a screening unit; 14-a positioning unit; 100-robot; 110-memory; a 120-processor; 130-a communication module; 131-a first antenna; 132-second antenna.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present invention.
The terms "comprises," "comprising," "including," or any other variation thereof, are intended to cover a specific feature, number, step, operation, element, component, or combination of the foregoing, which may be used in various embodiments of the present invention, and are not intended to first exclude the presence of or increase the likelihood of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing.
Furthermore, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and should not be construed as indicating or implying relative importance.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which various embodiments of the invention belong. The terms (such as those defined in commonly used dictionaries) will be interpreted as having a meaning that is the same as the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein in connection with the various embodiments of the invention.
The robot positioning method disclosed by the application is based on an Ultra Wide Band (UWB) wireless carrier communication technology, a phase difference of arrival (PDOA) principle and a high-frequency inertial measurement unit (Inertial measurement unit, IMU), and is used for accurately positioning a robot moving rapidly indoors with low calculation amount.
Ultra Wide Band (UWB) technology is a wireless carrier communication technology, which does not use a sinusoidal carrier, but uses non-sinusoidal narrow pulses of nanosecond level to transmit data, so that the spectrum occupied by the technology is Wide. The UWB technology has the advantages of low system complexity, low power spectrum density of the transmitted signal, insensitivity to channel fading, low interception capability, high positioning accuracy and the like, and is particularly suitable for indoor positioning of robots. In indoor positioning, UWB can achieve high ranging accuracy.
The UWB equipment based on PDOA ranging can output distance and angle values, and the positioning system based on PDOA-UWB can finish estimation of the position and the orientation of the robot. However, due to the limited time bandwidth, the PDOA-UWB can only measure the distance at the frequency of about 10Hz, and when the indoor robot moves rapidly, the position and the orientation estimated by the time-of-flight measurement and the phase measurement have larger errors. The PDOA-UWB and IMU are used for data fusion positioning, and high-frequency IMU data and low-frequency UWB pose measurement are combined, so that high-frequency and more accurate fusion positioning data can be obtained, and accurate positioning of the robot under rapid movement is facilitated.
Example 1
In one embodiment of the present application, as shown in fig. 1, a robot positioning method is provided, which includes the following steps:
s100: and acquiring the relative distance and the relative angle between the robot and each positioning label.
A plurality of positioning tags are arranged in advance in an active area of the robot, a communication module is arranged at a specific position of the robot, and each positioning tag sends pulse information (wireless carrier wave) to the communication module of the robot in real time. The robot can determine the relative distance and the relative angle between the robot and each positioning label according to the pulse information received by the communication module.
Furthermore, considering the advantages of strong penetrating power, low power consumption, good multipath resistance effect, high safety, low system complexity, capability of providing accurate positioning precision and the like of UWB, the relative distance and relative angle between the robot and each positioning label can be determined by utilizing the PDOA-UWB positioning technology. The PDOA-UWB communication module is arranged on the robot, a plurality of PDOA-UWB labels are arranged on a scene to be positioned, and the robot can acquire distance and angle data of each pair of labels and the communication module through a serial port.
It will be appreciated that the communication module may be mounted to a central location of the robot, the location of the communication module being representative of the location of the robot when the robot is positioned using the communication module and the respective tags. For example, a center point of one communication antenna of the communication module may be used as a coordinate origin, and a coordinate system may be established with a robot orientation as a positive direction of an X-axis (Y-axis is perpendicular to the X-axis, and the orientation of the Y-axis may not be limited) when the robot is stationary, under which a relative distance and a relative angle between the robot and each positioning tag are determined. The relative distance is the distance between the robot (i.e. the origin of coordinates) and the coordinates of the positioning tag, and can be determined according to the propagation speed and the propagation time of the pulse, and the relative angle is the included angle between the connecting line between the robot (i.e. the origin of coordinates) and the coordinates of the positioning tag and the connecting line between the positive X-axis coordinate axis.
S200: and acquiring inertial data of the robot.
The inertial data of the robot includes the linear acceleration and angular velocity of the robot at a certain moment. The linear acceleration and angular velocity of the robot at a certain moment can be acquired by means of a high frequency inertial measurement unit. It is understood that a high frequency inertial measurement unit is a device that measures the three-axis attitude angle or angular rate and acceleration of an object. In general, a three-axis gyroscope and three-direction accelerometers are installed in the high-frequency inertial measurement unit IMU, the gyroscope can acquire the angular velocity of the robot at a certain moment, and the accelerometer can acquire the linear acceleration of the robot at a certain moment. The robot can receive inertial data acquired by the IMU through a serial port.
S300: and estimating the estimated pose of the robot at the current moment according to the inertial data.
The linear acceleration in the inertial data acquired at the adjacent time may be integrated to estimate the speed and displacement variation of the robot at the adjacent time, and the angular velocity in the inertial data acquired at the adjacent time may be integrated to estimate the rotation variation of the robot at the adjacent time. And further, the variation and the rotation variation are added to the estimated pose displacement of the robot at the previous moment so as to estimate the estimated pose of the robot at the current moment.
S400: and determining a preset first number of angle reliable labels from the positioning labels according to the comparison result of the estimated angles in the estimated pose and the relative angles.
The method comprises the steps of selecting angle reliable labels from all positioning labels, sequentially traversing relative angles corresponding to all positioning labels, comparing all relative angles with estimated angles of estimated pose, calculating differences between all relative angles and estimated angles of estimated pose, sorting absolute values of the differences according to a sequence from small to large, selecting relative angles corresponding to N absolute values which are ranked forward, wherein N absolute values which are ranked forward are smaller than a preset angle threshold, and N is a preset first number. It can be understood that the relative angles corresponding to the N absolute values ranked forward are closest to the orientation of the robot, and therefore, the positioning labels corresponding to the N relative angles can be used as the angle reliable labels.
S500: and determining the actual pose of the robot at the current moment according to the relative distance and the relative angle corresponding to the preset first number of angle reliable labels.
Further, N angle reliable labels are screened, M distance reliable labels are selected from the N angle reliable labels according to the relative distance and the relative angle corresponding to the angle reliable labels, it can be understood that N is larger than or equal to M, and then the actual pose of the robot at the current moment is determined according to the N angle reliable labels and the M distance reliable labels.
It will be appreciated that the above step S100 may be performed after the step S300, and the order between determining the estimated pose and acquiring the relative distance and the relative angle between the robot and each positioning tag is not limited in this application.
According to the robot positioning method disclosed by the embodiment, the position relationship between the robot and each positioning tag is determined by utilizing carrier communication between the communication module of the robot and each positioning tag, the estimated pose of the robot at the current moment is estimated based on the inertial data of the robot, the angle reliable tag in each positioning tag is determined by the estimated angle of the estimated pose of the robot at the current moment, and the actual pose of the robot at the current moment is determined based on the relative distance and the relative angle corresponding to the angle reliable tag. According to the technical scheme, the high-frequency inertial measurement unit IMU is utilized to collect inertial data at a high frequency, and the inertial measurement unit IMU is used to collect inertial data when the robot moves, so that the IMU positioning and the communication module-tag positioning are fused, and accurate positioning is realized on the fast-moving robot. Compared with the fixed track positioning and the visual positioning based on the virtual track, the technical scheme has stronger practicability, does not need to install a guide rail and does not need special personnel to maintain the guide rail and the guide wire; compared with a mobile robot vision positioning method based on deep learning, the method has the advantages of smaller calculated amount, simple algorithm and convenience in calculation.
Example 2
Further, a first antenna and a second antenna may be installed at predetermined positions of the robot, where the first antenna and the second antenna may receive pulse signals transmitted by each positioning tag, and a relative distance and a relative angle between the robot and each positioning tag may be determined through steps shown in fig. 2:
s110: and acquiring a first distance between an ith positioning tag and the first antenna, wherein I is less than or equal to I, and I is the total number of the positioning tags.
S120: and acquiring a second distance between the ith positioning tag and the second antenna.
S130: and determining the arrival phase difference of the pulse signal sent by the ith positioning tag to the first antenna and the second antenna.
S140: and determining the relative distance and the relative angle between the robot and the ith positioning label according to the first distance, the arrival phase difference and the second distance.
As shown in fig. 3, O1 represents a first antenna of the robot, O2 represents a second antenna of the robot, and when the first antenna and the second antenna are installed on the robot, it is required to ensure that a ray connecting the first antenna and the second antenna can point to an orientation of the robot, that is, when the robot is stationary, an X-axis direction in fig. 3 represents an orientation of the robot (it is understood that a positive direction of an X-axis also changes when the orientation of the robot changes). Further, D represents the distance between O1 and O2, D is known as a represents the positioning tag, the distance from O1 to a is R, the distance from O2 to a is R-P, and P can be calculated from the arrival phase difference of the pulse signals from a to O1 and O2. It will be appreciated that the number of components, 
The arrival phase difference of the pulse signal from a to O1 and O2 is shown, and λ is the wavelength of the pulse signal. />
Further, θ1 is calculated, and as can be seen from fig. 3: the perpendicular segments of O2 to O1A correspond to two right triangles, and can be deduced according to the Pythagorean theorem:
(R-P) 2 -(R-(P+a)) 2 ＝D 2 -(P+a) 2 then p+a= (D) 2 -P 2 +2RP)/2R, further derived according to the cosine law,
because the first antenna and the second antenna are arranged at the specific position of the robot, the first antenna can be arranged at the central position of the robot when the first antenna is arranged, and the rays connected with the first antenna and the second antenna can be ensured to point to the direction of the robot, and the direction of the robot is taken as the positive direction of the X axis, so that when the robot is stationary, the angle theta 1 The relative angle between the robot and the positioning tag A can be used, and the relative distance between the robot and the positioning tag A can be used as R.
Further, according to the principle shown in fig. 3, the relative distance and the relative angle between the robot and each positioning tag are respectively determined, and the determined relative distances and the determined relative angles are fed back to the robot, so that the robot can determine the actual pose of the robot according to the relative distances and the relative angles.
Example 3
In one embodiment of the present application, as shown in fig. 4, estimating an estimated pose of the robot at a current moment according to the inertial data includes the following steps:
s310: and estimating the displacement variation of the robot from the last moment to the current moment according to the linear acceleration of the last moment in the inertial data.
The last moment can be represented as a t-1 moment, the current moment can be represented as a t moment, and because the IMU for acquiring the inertial data of the robot has high-frequency acquisition capability, the interval between the t-1 moment and the t moment is very short, when the estimated pose of the t moment is estimated by utilizing the inertial data of the t-1 moment, the estimation error can be effectively reduced, and the positioning precision of the robot can be further effectively improved.
For linear acceleration a in inertial data acquired at time t-1 t-1 Integrating can determine the speed and displacement variation of the robot at the time t. Exemplary speed of robot at time t
Displacement variation of robot at time t>
S320: and estimating the angle change quantity of the robot from the last moment to the current moment according to the angular speed at the last moment in the inertia data.
For linear acceleration w in inertial data acquired at time t-1 t-1 Integrating can determine the angle change of the robot at the time t. Exemplary, the amount of angular variation of the robot at time t
S330: and estimating the estimated pose of the robot at the current moment according to the displacement variation and the angle variation.
Accumulating the displacement variation to the actual position corresponding to the actual pose of the robot at the previous moment to estimate the estimated position corresponding to the actual pose of the robot at the current moment; and accumulating the angle change quantity to an actual angle corresponding to the actual pose of the robot at the previous moment so as to estimate an estimated angle corresponding to the actual pose of the robot at the current moment, and further estimating the estimated pose of the robot at the current moment according to the estimated position and the estimated angle. So that the robot can position the actual pose of the current moment of the robot according to the estimated pose of the current moment determined by the IMU. The high-frequency acquisition function of the IMU can pre-estimate the estimated pose of the robot at the current moment of the fast moving robot, ensure that the deviation between the estimated pose and the actual pose is smaller, and further ensure that the fast moving robot is accurately positioned.
Example 4
In one embodiment of the present application, as shown in fig. 5, determining an angle reliable tag includes the steps of:
S410: and calculating the absolute value of the difference between the relative angle corresponding to the ith positioning label and the estimated angle, wherein I is less than or equal to I, and I is the total number of the positioning labels.
S420: and judging whether the absolute value is larger than a preset angle threshold value.
If the angle threshold is smaller than or equal to the angle threshold, executing step S430; if the angle threshold is greater than the angle threshold, step S440 is performed. And determining an angle reliable label from the I positioning labels so as to position the robot by using the angle reliable label.
S430: the ith positioning tag is determined to be reliable.
S440: the ith location tag is unreliable.
Exemplary, as shown in fig. 6, O1 represents a first antenna of the robot, O2 represents a second antenna of the robot, and the positive direction of the X-axis represents the corresponding real-time estimated direction of the robot when positioning based on the communication module-tag, but since the time bandwidth based on the communication module-tag positioning is limited, for example, PDOA-UWB can only measure distance at a frequency of about 10Hz, there is a large error in both the position and direction estimated by the time-of-flight measurement and the phase measurement when the indoor robot moves fast, therefore, the present embodiment uses the high frequency inertia measurement unit to determine the estimated angle θ in the estimated pose at the current time 0 By combining theta 0 Relative angle θ to positioning tag A 1 The absolute value of the difference is compared with a preset angle threshold to determine whether the locating tag a is an angle reliable tag. And respectively judging each positioning label by using the judging method, and determining the angle reliable label from each positioning label. Each positioning label is screened through the angle threshold value, the positioning label with large angle error is filtered and removed, and the robot is positioned based on the rest angle reliable label, so that the calculated amount of the robot positioning process is effectively reduced, and the robot moving fast can be accurately positioned.
Example 5
In one embodiment of the present application, as shown in fig. 7, determining the actual pose of the robot at the current moment includes the following steps:
s510: and calculating the mean value corresponding to the relative angle and the variance corresponding to the relative angle according to the relative angles corresponding to the preset first number of angle reliable labels.
And calculating the mean value corresponding to the relative angle and the variance corresponding to the relative angle according to the relative angles corresponding to the N reliable angle labels.
S520: and determining a predetermined second number of distance reliable labels according to the relative distances corresponding to the predetermined first number of angle reliable labels.
S530: and calculating the mean value corresponding to the relative distance and the variance corresponding to the relative distance according to the relative distance degree corresponding to the preset second number of distance reliable labels.
S540: and inputting the average value corresponding to the relative angle, the average value corresponding to the relative distance, the variance corresponding to the relative angle and the variance corresponding to the relative distance into a preset unscented Kalman filter to obtain the actual pose of the robot at the current moment.
The mean value corresponding to the relative angle and the mean value corresponding to the relative distance are input as measured values of the actual pose of the robot, the variance corresponding to the relative angle is the uncertainty of the angle in the measured values corresponding to the actual pose of the robot, and the variance corresponding to the relative distance is the uncertainty of the position in the measured values corresponding to the actual pose of the robot. The unscented kalman filter can judge whether the measured value corresponding to the actual pose of the robot is reliable according to the input average value corresponding to the relative angle, the average value corresponding to the relative distance, the variance corresponding to the relative angle and the variance corresponding to the relative distance, for example, if the variance corresponding to the relative distance is smaller, the average value corresponding to the relative distance is reliable, the variance corresponding to the relative angle is smaller, the average value corresponding to the relative angle is reliable, that is, the measured value of the actual pose of the robot determined by the average value corresponding to the relative distance and the average value corresponding to the relative angle is reliable, and when the unscented kalman filter is used for positioning, the actual pose of the robot at the current moment is biased to the measured value of the actual pose of the robot; otherwise, if the variance corresponding to the relative distance is larger, the mean value corresponding to the relative distance is not credible, and if the variance corresponding to the relative angle is larger, the mean value corresponding to the relative angle is not credible, namely, the mean value corresponding to the relative distance and the measured value of the actual pose of the robot, which is determined by the mean value corresponding to the relative angle, are not credible, and when the unscented Kalman filter is used for positioning, the actual pose of the robot at the current moment is far away from the measured value of the actual pose of the robot.
It can be understood that the actual pose of the robot at the current moment is determined by using the unscented Kalman filter, the Jacobian matrix is not required to be analyzed and calculated by a system equation, and the system equation has higher precision and more convenient calculation in nonlinear optimization, so that the robot is positioned more accurately and the positioning process is more convenient.
Further, as shown in fig. 8, determining the distance reliable tag in step S520 includes the steps of:
s521: the predetermined first number of angularly reliable tags is divided into K groups, each group comprising at least 3 angularly reliable tags.
It will be appreciated that if the total number of angle reliable tags is N, each group includes p, p being greater than or equal to 3, then K groups can be determined using the permutation and combination formula,
s522: the position of the robot is determined from the angularly reliable tags of each group.
The position of the robot can be determined based on any 3 angle reliable labels of each group by using a triangle positioning method, and the corresponding positions of each group are calculated respectively, so that K positions can be determined. Triangle positioning is a common technical means in the positioning field, and is not further explained herein.
S523: and calculating the mean value corresponding to the K positions and the variance corresponding to the K positions.
S524: if the variance corresponding to the K positions is larger than a preset variance threshold, deleting the position farthest from the mean value corresponding to the K positions in the K positions, and recalculating the mean value corresponding to the K-1 position and the variance corresponding to the K-1 position until the variance corresponding to the residual positions is smaller than or equal to the preset variance threshold, wherein the positioning label corresponding to the residual positions is a distance reliable label.
S525: if the variance corresponding to the K positions is smaller than or equal to a preset variance threshold, the positioning labels corresponding to the K positions are distance reliable labels.
The embodiment discloses a method for further screening angle reliable labels, which comprises the steps of selecting distance reliable labels from the angle reliable labels, and inputting the average value corresponding to the relative angle, the average value corresponding to the relative distance, the variance corresponding to the relative angle and the variance corresponding to the relative distance of each distance reliable label into a preset unscented Kalman filter to obtain the actual pose of the robot at the current moment. It can be appreciated that the unscented kalman filter has the advantages that the system equation does not need to be analyzed and calculated to obtain the jacobian matrix, the jacobian matrix has higher precision in nonlinear optimization, and calculation is more convenient and simple, and the unscented kalman filter effectively reduces the complexity of robot positioning, so that the positioning process is more efficient and quick.
Example 6
In one embodiment of the present application, as shown in fig. 9, a robotic positioning device 10 includes: an acquisition unit 11, an estimation unit 12, a screening unit 13 and a positioning unit 14.
An obtaining unit 11, configured to obtain a relative distance and a relative angle between a robot and each positioning tag, where the robot includes a communication module, and the communication module is configured to receive a pulse signal sent by each positioning tag; an acquiring unit 11, configured to acquire inertial data of the robot; an estimating unit 12 for estimating an estimated pose of the robot at a current time based on inertial data; a screening unit 13, configured to determine a predetermined first number of angle reliable tags from the positioning tags according to a comparison result of the estimated angle in the estimated pose and each of the relative angles; and the positioning unit 14 is used for determining the actual pose of the robot at the current moment according to the relative distance and the relative angle corresponding to the preset first number of angle reliable labels.
Further, a first antenna and a second antenna may be installed at a predetermined position of the robot, where the first antenna and the second antenna are configured to receive pulse signals sent by each positioning tag, and the acquiring a relative distance and a relative angle between the robot and each positioning tag includes: acquiring a first distance between an ith positioning tag and the first antenna, wherein I is less than or equal to I, and I is the total number of the positioning tags; acquiring a second distance between an ith positioning tag and the second antenna; determining an arrival phase difference of a pulse signal sent by an ith positioning tag to the first antenna and the second antenna; and determining the relative distance and the relative angle between the robot and the ith positioning label according to the first distance, the arrival phase difference and the second distance.
Further, the inertial data includes linear acceleration and angular velocity of the robot, and the estimating the estimated pose of the robot at the current moment according to the inertial data includes: estimating the displacement variation of the robot from the last moment to the current moment according to the linear acceleration of the last moment in the inertial data; estimating the angle change quantity of the robot from the last moment to the current moment according to the angular speed at the last moment in the inertial data; and estimating the estimated pose of the robot at the current moment according to the displacement variation and the angle variation.
Further, the determining a predetermined first number of angle reliable labels from the positioning labels according to the comparison result of the estimated angle in the estimated pose and each relative angle includes: calculating the absolute value of the difference between the relative angle corresponding to the ith positioning label and the estimated angle, wherein I is less than or equal to I, and I is the total number of the positioning labels; judging whether the absolute value is larger than a preset angle threshold value or not; if the angle threshold value is smaller than or equal to the angle threshold value, the ith positioning label is reliable; if the angle threshold is larger than the angle threshold, the ith positioning label is unreliable.
Further, the determining the actual pose of the robot at the current moment according to the relative distance and the relative angle corresponding to the predetermined first number of angle reliable labels includes: calculating a mean value corresponding to the relative angle and a variance corresponding to the relative angle according to the relative angles corresponding to the preset first number of angle reliable labels; determining a predetermined second number of distance-reliable labels according to the relative distances corresponding to the predetermined first number of angle-reliable labels; calculating a mean value corresponding to the relative distance and a variance corresponding to the relative distance according to the relative distance degree corresponding to the preset second number of distance reliable labels; and inputting the average value corresponding to the relative angle, the average value corresponding to the relative distance, the variance corresponding to the relative angle and the variance corresponding to the relative distance into a preset unscented Kalman filter to obtain the actual pose of the robot at the current moment.
Further, the determining the predetermined second number of distance-reliable labels according to the relative distances corresponding to the predetermined first number of angle-reliable labels includes: dividing the predetermined first number of angularly reliable tags into K groups, each group comprising at least 3 angularly reliable tags; determining the position of the robot according to the angle reliable labels of each group; calculating the mean value corresponding to the K positions and the variance corresponding to the K positions; if the variance corresponding to the K positions is larger than a preset variance threshold, deleting the position farthest from the average value corresponding to the K positions in the K positions, and recalculating the average value corresponding to the K-1 positions and the variance corresponding to the K-1 positions until the variance corresponding to the residual positions is smaller than or equal to the preset variance threshold, wherein the positioning label corresponding to the residual positions is a distance reliable label; if the variance corresponding to the K positions is smaller than or equal to a preset variance threshold, the positioning labels corresponding to the K positions are distance reliable labels.
The robot positioning device 10 disclosed in the present application is configured to execute the robot positioning method described in the above embodiment through the cooperation of the acquisition unit 11, the estimation unit 12, the screening unit 13 and the positioning unit 14, and the implementation and the beneficial effects related to the above embodiment are also applicable in the present embodiment, and are not repeated herein.
In one embodiment of the present application, as shown in fig. 10, a robot 100 is provided, including a memory 110, a processor 120, and a communication module 130, where the memory 110 stores a computer program, and the computer program executes the robot positioning method described in the present application when running on the processor 120, and the communication module 130 is configured to receive pulse signals sent by each positioning tag.
Further, the communication module 130 includes a first antenna 131 and a second antenna 132, and the communication module 130 receives the pulse signals transmitted by the respective positioning tags by using the first antenna 131 and the second antenna 132.
One embodiment of the present application proposes a readable storage medium storing a computer program which, when run on a processor, performs the robot positioning method described herein.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other manners as well. The apparatus embodiments described above are merely illustrative, for example, of the flow diagrams and block diagrams in the figures, which illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules or units in various embodiments of the invention may be integrated together to form a single part, or the modules may exist alone, or two or more modules may be integrated to form a single part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a smart phone, a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned readable storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention.
Claims (9)
1. A method for positioning a robot, the robot comprising a communication module for receiving pulse signals transmitted by respective positioning tags, the method comprising:
acquiring relative distances and relative angles between the robot and each positioning label;
acquiring inertial data of the robot;
estimating the estimated pose of the robot at the current moment according to the inertial data;
determining a predetermined first number of angle reliable labels from the positioning labels according to the comparison result of the estimated angles in the estimated pose and the relative angles;
calculating a mean value corresponding to the relative angle and a variance corresponding to the relative angle according to the relative angles corresponding to the preset first number of angle reliable labels;
determining a predetermined second number of distance-reliable labels according to the relative distances corresponding to the predetermined first number of angle-reliable labels;
calculating a mean value corresponding to the relative distance and a variance corresponding to the relative distance according to the relative distance degree corresponding to the preset second number of distance reliable labels;
and inputting the average value corresponding to the relative angle, the average value corresponding to the relative distance, the variance corresponding to the relative angle and the variance corresponding to the relative distance into a preset unscented Kalman filter to obtain the actual pose of the robot at the current moment.
2. The robot positioning method according to claim 1, wherein a first antenna and a second antenna are installed at predetermined positions of the robot, the first antenna and the second antenna are used for receiving pulse signals sent by the positioning tags, and the acquiring the relative distance and the relative angle between the robot and the positioning tags includes:
acquiring a first distance between an ith positioning tag and the first antenna, wherein I is less than or equal to I, and I is the total number of the positioning tags;
acquiring a second distance between an ith positioning tag and the second antenna;
determining an arrival phase difference of a pulse signal sent by an ith positioning tag to the first antenna and the second antenna;
and determining the relative distance and the relative angle between the robot and the ith positioning label according to the first distance, the arrival phase difference and the second distance.
3. The robot positioning method according to claim 1, wherein the inertial data includes linear acceleration and angular velocity of the robot, and the estimating the estimated pose of the robot at the current time from the inertial data includes:
estimating the displacement variation of the robot from the last moment to the current moment according to the linear acceleration of the last moment in the inertial data;
Estimating the angle change quantity of the robot from the last moment to the current moment according to the angular speed at the last moment in the inertial data;
and estimating the estimated pose of the robot at the current moment according to the displacement variation and the angle variation.
4. The method of claim 1, wherein said determining a predetermined first number of angularly reliable tags from said respective location tags based on a comparison of an estimated angle in said estimated pose and respective said relative angles, comprises:
calculating the absolute value of the difference between the relative angle corresponding to the ith positioning label and the estimated angle, wherein I is less than or equal to I, and I is the total number of the positioning labels;
judging whether the absolute value is larger than a preset angle threshold value or not;
if the angle threshold value is smaller than or equal to the angle threshold value, the ith positioning label is reliable;
if the angle threshold is larger than the angle threshold, the ith positioning label is unreliable.
5. The method of claim 1, wherein determining the predetermined second number of distance-reliable tags based on the relative distances corresponding to the predetermined first number of angle-reliable tags comprises:
dividing the predetermined first number of angularly reliable tags into K groups, each group comprising at least 3 angularly reliable tags;
Determining the position of the robot according to the angle reliable labels of each group;
calculating the mean value corresponding to the K positions and the variance corresponding to the K positions;
if the variance corresponding to the K positions is larger than a preset variance threshold, deleting the position farthest from the average value corresponding to the K positions in the K positions, and recalculating the average value corresponding to the K-1 positions and the variance corresponding to the K-1 positions until the variance corresponding to the residual positions is smaller than or equal to the preset variance threshold, wherein the positioning label corresponding to the residual positions is a distance reliable label;
if the variance corresponding to the K positions is smaller than or equal to a preset variance threshold, the positioning labels corresponding to the K positions are distance reliable labels.
6. A robotic positioning device, the robot comprising a communication module for receiving pulse signals transmitted by respective positioning tags, the device comprising:
the acquisition unit is used for acquiring the relative distance and the relative angle between the robot and each positioning label; the inertial data acquisition module is also used for acquiring inertial data of the robot;
the estimating unit is used for estimating the estimated pose of the robot at the current moment according to the inertial data;
a screening unit, configured to determine a predetermined first number of angle reliable tags from the positioning tags according to comparison results of the estimated angles and the respective relative angles in the estimated pose;
The positioning unit is used for calculating a mean value corresponding to the relative angle and a variance corresponding to the relative angle according to the relative angles corresponding to the preset first number of angle reliable labels;
determining a predetermined second number of distance-reliable labels according to the relative distances corresponding to the predetermined first number of angle-reliable labels;
calculating a mean value corresponding to the relative distance and a variance corresponding to the relative distance according to the relative distance degree corresponding to the preset second number of distance reliable labels;
and inputting the average value corresponding to the relative angle, the average value corresponding to the relative distance, the variance corresponding to the relative angle and the variance corresponding to the relative distance into a preset unscented Kalman filter to obtain the actual pose of the robot at the current moment.
7. The robotic positioning device of claim 6, wherein the communication module includes a first antenna and a second antenna, the first antenna and the second antenna configured to receive the pulse signals sent by the respective positioning tags, the acquiring the relative distance and the relative angle between the robot and the respective positioning tags, comprising:
acquiring a first distance between an ith positioning tag and the first antenna, wherein I is less than or equal to I, and I is the total number of the positioning tags;
Acquiring a second distance between an ith positioning tag and the second antenna;
determining an arrival phase difference of a pulse signal sent by an ith positioning tag to the first antenna and the second antenna;
and determining the relative distance and the relative angle between the robot and the ith positioning label according to the first distance, the arrival phase difference and the second distance.
8. A robot comprising a memory, a processor and a communication module, the memory storing a computer program which, when run on the processor, performs the robot positioning method of any of claims 1 to 5, and the communication module is adapted to receive the pulse signals sent by the respective positioning tags.
9. A readable storage medium, characterized in that it stores a computer program which, when run on a processor, performs the robot positioning method of any of claims 1 to 5.
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