CN114545944B - AGV course positioning navigation method based on magnetic nail magnetic field intensity correction - Google Patents
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Abstract
The invention discloses an AGV course positioning navigation method based on magnetic nail magnetic field intensity correction, which comprises the steps of arranging magnetic nails according to a certain interval according to path planning, arranging a magnetic ruler sensor in front of an AGV head, and horizontally paving an inertial measurement unit in the AGV; then dividing the magnetic field intensity scanned by the magnetic sensor into areas along the longitudinal direction and the transverse direction of the vehicle body, and calibrating the magnetic field intensity level; and finally, measuring the angular speed and the speed of the vehicle between the magnetic nails by using an inertial sensor so as to predict the pose and realize vehicle control. According to the invention, the inertial navigation control and the magnetic nail navigation based on the magnetic field intensity are fused, so that the high-precision positioning control is realized.
Description
Technical Field
The invention belongs to the field of automatic guided vehicle positioning and navigation, and particularly relates to a method for acquiring higher positioning accuracy by analyzing the magnetic field intensity of a magnetic nail when the magnetic nail is used for correcting the pose of an automatic guided vehicle.
Background
With advances in science and technology, physical manufacturing facilities are gradually turning to intelligent, unmanned, automated Guided Vehicles (AGVs) as an intelligent industrial device, and are widely used in various industries. The navigation positioning technology is the basis of autonomous movement of the AGV, and at present, the main methods of mobile robot navigation include magnetic navigation, optical navigation, laser navigation, inertial navigation and the like. In the magnetic nail navigation application on the current market, the magnetic scale sensor can detect the magnetic field intensity when approaching to the magnetic nail, at the moment, the center of the magnetic scale sensor does not actually reach the position above the magnetic nail, if the vehicle body is judged to be recognized as the magnetic nail, namely, the vehicle body reaches the preset position, obvious positioning errors are obviously caused, and thus the development difficulty of control is increased.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an AGV course positioning navigation method based on magnetic nail magnetic field intensity correction, so that inertial navigation control and magnetic nail navigation based on magnetic field intensity can be fused to realize higher-precision positioning, thereby achieving the purpose that an automatic guided vehicle can reach a target position more accurately in practical application.
In order to achieve the aim of the invention, the invention adopts the following technical scheme:
the AGV course positioning navigation method based on magnetic nail magnetic field intensity correction is characterized in that the method is applied to a working scene of an AGV for navigation according to a planned path, and magnetic nails are arranged on the planned path at certain intervals; the AGV adopts double-wheel differential drive, and is provided with a virtual front wheel at the position of a headstock on a center line of a connecting line of the circle centers of two differential wheels, a magnetic scale sensor is arranged in front of the headstock of the AGV, and an inertial measurement unit is horizontally arranged in the AGV; the positioning navigation method comprises the following steps:
step 1: constructing a coordinate system by using the circumscribed rectangle of the working scene, and enabling the anticlockwise direction taking the x axis of the coordinate system as a reference to be a positive direction;
Defining and initializing a time k=1; marking a centroid pose of an initial k moment in the coordinate system as (x k,yk,θk) and taking the centroid pose as a departure point of the AGV on a planned path, wherein x k and y k represent position coordinates of the k moment in the coordinate system, and theta k is a running direction of the k moment;
Setting the minimum magnetic field strength triggered by the magnetic nails as H min, dividing the magnetic field strength along the vertical direction of the magnetic scale sensor into 2 grade ranges, wherein the first grade range is H min—H1, and the second grade range is H 1—H2; wherein H 1 represents the minimum magnetic field strength for triggering the AGV to correct the pose, and H 2 represents the maximum magnetic field strength for magnetic nail detection;
Step 2: setting the maximum value of the mass center speed of the AGV as v max, starting the AGV to drive forwards according to a planned path from an outgoing point at a fixed acceleration alpha, calculating the k moment mass center speed v (k) of the AGV according to v (k) =v (k-1) +alpha×delta T, wherein v (k) is less than or equal to v max, and delta T represents a unit sampling time interval between two adjacent moments; let centroid speed v (k-1) =0 for the departure point when k=1;
step 3: judging whether a magnetic ruler sensor on the AGV detects magnetic nails on a planned path at the moment k, if so, executing the step 4; otherwise, measuring the centroid angular velocity w (k) at the moment k by using inertial navigation, and executing the step 6;
Step 4: judging whether the magnetic field intensity of the detected magnetic nails is in a first-level range, if so, indicating that the AGV normally runs according to the planned path, and not correcting the deviation-free navigation; and executing the step 6; otherwise, the magnetic field intensity of the detected magnetic nails is in a second-stage range, the angular deviation phi (k) of the current head direction of the vehicle at the moment k, deviating from the planned route, is obtained by utilizing a PID algorithm according to the position deviation C (k) of the moment k measured by the ruler sensor, and the step 5 is executed;
step 5: calculating the corrected centroid angular velocity W (k) of the AGV at the moment k by using the formula (1) and assigning the corrected centroid angular velocity W (k) to W (k):
W(k)＝v(k)×tan(φ(k))/L (1)
In the formula (1), L is the distance between the virtual front wheel and the middle line of the differential speed wheel;
Step 6: obtaining a wheel speed V L (k) of a left differential wheel and a wheel speed V R (k) of a right differential wheel of the AGV by using the formula (2), so that the AGV runs on the planned path according to the calculated wheel speed:
in the formula (2), B is the distance between the left differential wheel and the right differential wheel, and M is the diameter of the differential wheel;
Step 7: the wheel speed V L (k+1) fed back by the left differential wheel of the AGV at the moment k+1 and the wheel speed V R (k+1) fed back by the right differential wheel are fed back by the double-wheel differential driving motor, so that the centroid angular speed w (k+1) and the centroid speed V (k+1) of the AGV at the moment k+1 are calculated by using the formula (3):
Step 8: establishing a motion equation of the AGV according to the formula (4), and obtaining a centroid pose X (k+1) = (X k+1,yk+1,θk+1)T) of the AGV at the moment k+1:
In the formula (3), X (k) = (X k,yk,θk)T is the centroid pose of the AGV at the moment k, D (k) is the displacement of the AGV on a straight line in the unit sampling time interval of the moment k and the moment k+1, and D (k) = v (k) ×DeltaT, delta (k) is the angular displacement of the AGV in the unit sampling time interval of the moment k and the moment k+1, and delta (k) = w (k) ×DeltaT;
Step 9: after k is assigned to k, returning to the step 3 until the position coordinate at the current moment reaches the target position.
Compared with the prior art, the invention has the beneficial effects that:
1. According to the invention, the magnetic field intensity of the detected magnetic nails is analyzed, the threshold range is defined by taking the maximum value of the magnetic field intensity as the center to divide the grade and the positioning correction area, the judgment condition of positioning information is enhanced, the magnetic nails are more accurately identified by the magnetic sensor, and the precision positioning efficiency is improved.
2. The invention defines the threshold range for the highest level to realize the adjustability of the positioning precision.
3. When inertial navigation is combined, the invention corrects the positioning correction information at the magnetic nails with higher precision, corrects the accumulated error, can lead the automatic guided vehicle to have a more accurate initial value to calculate the inertial navigation position and posture after the automatic guided vehicle drives away from the magnetic nails, and leads the unmanned robot navigation to obtain more accurate positioning information in engineering practice.
Drawings
FIG. 1 is a schematic view of a magnetic tack scan;
FIG. 2 is a graph of the magnetic nail correction of the present invention to obtain directional bias and left and right wheel speeds;
Fig. 3 is a schematic view of inertial navigation estimation.
Detailed Description
In this embodiment: the AGV course positioning navigation method based on magnetic nail magnetic field intensity correction is applied to a working scene of the AGV for navigation according to a planned path, magnetic nails are arranged on the planned path at certain intervals, other ferromagnetic objects cannot be arranged around the planned path, and obstacles cannot be arranged on a moving path; the AGV adopts double-wheel differential drive, a virtual front wheel is supposed to be arranged at the position of the head on the center line of the connecting line of the circle centers of the two differential wheels, a magnetic scale sensor (which is not more than 50mm away from the ground) is arranged in front of the head of the AGV, a non-magnetic material is needed to be used for the mounting plate, and the background magnetic field strength is not more than 1 Gauss; an inertial measurement unit is horizontally arranged in the AGV, and the following points should be noted when the inertial sensor is installed:
Firstly, to ensure that the sensor mounting surface is in complete abutment with the surface to be measured, the surface to be measured is as horizontal as possible. Secondly, the bottom line of the sensor and the axis of the measured object cannot form an included angle, and the bottom line of the sensor is kept parallel or orthogonal to the rotation axis of the measured object during installation. Finally, the mounting surface of the sensor and the measured surface must be fixed tightly, contact smoothly and rotate stably, and measurement errors caused by acceleration and vibration are avoided.
In this embodiment, the positioning and navigation method is performed according to the following steps:
Step 1: constructing a coordinate system by using an external rectangle of the working scene, and enabling the anticlockwise direction taking the x axis of the coordinate system as a reference to be a positive direction;
Defining and initializing a time k=1; marking a centroid pose of an initial k moment in a coordinate system as (x k,yk,θk) and taking the centroid pose as a departure point of the AGV on a planned path, wherein x k and y k represent position coordinates of the k moment in the coordinate system, and theta k is a running direction of the k moment; in addition, the task to be executed is associated with the marked position in the coordinate system, and the AGV enters the task point area to execute the corresponding task;
The sensor adopts a magnetic scale sensor with 32 Hall detection points, the distance between measurement points is 10mm, the detection height is 0-50mm, the serial numbers of the detection points from left to right are sequentially 1-32, the detection precision is 1mm, the detection range is 0-320mm, N poles or S poles can be identified, 36 detection points respectively detect current magnetic field intensity signals, corresponding values are output, the magnetic field intensity data range detected at each position is from-2048 to +2048 gauss, the N pole magnetic field signal is a negative value, and the S pole magnetic field signal is a positive value. The 36 detection points along the parallel direction of the sensor return corresponding magnetic field strength when the magnetic nails are detected. As shown in fig. 1;
Setting the minimum magnetic field strength triggered by the magnetic nails as H min, dividing the magnetic field strength along the vertical direction of the magnetic scale sensor into 2 grade ranges, wherein the first grade range is H min—H1, and the second grade range is H 1—H2; wherein H 1 represents the minimum magnetic field strength for triggering the AGV to correct the pose, and H 2 represents the maximum magnetic field strength for magnetic nail detection;
Step 2: setting the maximum value of the mass center speed of the AGV as v max, starting the AGV to drive forwards according to a planned path from an outgoing point at a fixed acceleration alpha, calculating the k moment mass center speed v (k) of the AGV according to v (k) =v (k-1) +alpha×delta T, wherein v (k) is less than or equal to v max, and delta T represents a unit sampling time interval between two adjacent moments; let centroid speed v (k-1) =0 for the departure point when k=1;
step 3: judging whether a magnetic ruler sensor on the AGV detects magnetic nails on a planned path at the moment k, if so, executing the step 4; otherwise, measuring the centroid angular velocity w (k) at the moment k by using inertial navigation, and executing the step 6;
Step 4: judging whether the magnetic field intensity of the detected magnetic nails is in a first-level range, if so, indicating that the AGV normally runs according to the planned path, and not correcting the deviation-free navigation; and executing the step 6; otherwise, the magnetic field intensity of the detected magnetic nails is in a second-stage range, the angular deviation phi (k) of the current head direction of the vehicle at the moment k, deviating from the planned route, is obtained by utilizing a PID algorithm according to the position deviation C (k) of the moment k measured by the ruler sensor, and the step 5 is executed;
Step 5: as shown in fig. 2, wherein DirF is the virtual front wheel direction angle; virtual front wheel distance differential wheel middle line distance; b is the distance between the left differential wheel and the right differential wheel; v1 is the longitudinal travel speed; v2 is the normal velocity; v is the AGV centroid speed; w is the angular velocity of the AGV centroid; n1, w1 are the left wheel rotational linear and angular speeds; n2, w2 are right wheel rotational linear and angular speeds;
calculating the corrected centroid angular velocity W (k) of the AGV at the moment k by using the formula (1) and assigning the corrected centroid angular velocity W (k) to W (k):
W(k)＝v(k)×tan(φ(k))/L (1)
In the formula (1), L is the distance between the virtual front wheel and the middle line of the differential speed wheel;
Step 6: obtaining a wheel speed V L (k) of a left differential wheel and a wheel speed V R (k) of a right differential wheel of the AGV by using the formula (2), so that the AGV runs on the planned path according to the calculated wheel speed:
in the formula (2), B is the distance between the left differential wheel and the right differential wheel, and M is the diameter of the differential wheel;
Step 7: the wheel speed V L (k+1) fed back by the left differential wheel of the AGV at the moment k+1 and the wheel speed V R (k+1) fed back by the right differential wheel are fed back by the double-wheel differential driving motor, so that the centroid angular speed w (k+1) and the centroid speed V (k+1) of the AGV at the moment k+1 are calculated by using the formula (3):
Step 8: establishing a motion equation of the AGV according to the formula (4), and obtaining a centroid pose X (k+1) = (X k+1,yk+1,θk+1)T) of the AGV at the moment k+1:
In the formula (3), X (k) = (X k,yk,θk)T is the centroid pose of the AGV at the k moment, D (k) is the displacement of the AGV on a straight line in the unit sampling time interval of the k moment and the k+1 moment, and D (k) = v (k) ×Δt, delta (k) is the angular displacement of the AGV in the unit sampling time of the k moment and the k+1 moment, and delta (k) = w (k) ×Δt, as shown in fig. 3;
Step 9: calculating the linear distance between the real-time pose and the position of the task point through the real-time pose obtained in the step 8, stopping the vehicle to execute the corresponding task if the vehicle enters a certain task point area, and returning to the step 2 after the task is finished; if a certain task point area is not entered, assigning k+1 to k, and returning to the step 3 until the position coordinate at the current moment reaches the target position.
Claims (1)
1. The AGV course positioning navigation method based on magnetic nail magnetic field intensity correction is characterized by being applied to a working scene of an AGV for navigation according to a planned path, and magnetic nails are arranged on the planned path at certain intervals; the AGV adopts double-wheel differential drive, and is provided with a virtual front wheel at the position of a headstock on a center line of a connecting line of the circle centers of two differential wheels, a magnetic scale sensor is arranged in front of the headstock of the AGV, and an inertial measurement unit is horizontally arranged in the AGV; the positioning navigation method comprises the following steps:
step 1: constructing a coordinate system by using the circumscribed rectangle of the working scene, and enabling the anticlockwise direction taking the x axis of the coordinate system as a reference to be a positive direction;
Defining and initializing a time k=1; marking a centroid pose of an initial k moment in the coordinate system as (x k,yk,θk) and taking the centroid pose as a departure point of the AGV on a planned path, wherein x k and y k represent position coordinates of the k moment in the coordinate system, and theta k is a running direction of the k moment;
Setting the minimum magnetic field strength triggered by the magnetic nails as H min, dividing the magnetic field strength along the vertical direction of the magnetic scale sensor into 2 grade ranges, wherein the first grade range is H min—H1, and the second grade range is H 1—H2; wherein H 1 represents the minimum magnetic field strength for triggering the AGV to correct the pose, and H 2 represents the maximum magnetic field strength for magnetic nail detection;
Step 2: setting the maximum value of the mass center speed of the AGV as v max, starting the AGV to drive forwards according to a planned path from an outgoing point at a fixed acceleration alpha, calculating the k moment mass center speed v (k) of the AGV according to v (k) =v (k-1) +alpha×delta T, wherein v (k) is less than or equal to v max, and delta T represents a unit sampling time interval between two adjacent moments; let centroid speed v (k-1) =0 for the departure point when k=1;
step 3: judging whether a magnetic ruler sensor on the AGV detects magnetic nails on a planned path at the moment k, if so, executing the step 4; otherwise, measuring the centroid angular velocity w (k) at the moment k by using inertial navigation, and executing the step 6;
Step 4: judging whether the magnetic field intensity of the detected magnetic nails is in a first-level range, if so, indicating that the AGV normally runs according to the planned path, and not correcting the deviation-free navigation; and executing the step 6; otherwise, the magnetic field intensity of the detected magnetic nails is in a second-stage range, the angular deviation phi (k) of the current head direction of the vehicle at the moment k, deviating from the planned path, is obtained by utilizing a PID algorithm according to the position deviation C (k) of the moment k measured by the ruler sensor, and the step 5 is executed;
step 5: calculating the corrected centroid angular velocity W (k) of the AGV at the moment k by using the formula (1) and assigning the corrected centroid angular velocity W (k) to W (k):
W(k)＝v(k)×tan(φ(k))/L (1)
In the formula (1), L is the distance between the virtual front wheel and the middle line of the differential speed wheel;
Step 6: obtaining a wheel speed V L (k) of a left differential wheel and a wheel speed V R (k) of a right differential wheel of the AGV by using the formula (2), so that the AGV runs on the planned path according to the calculated wheel speed:
in the formula (2), B is the distance between the left differential wheel and the right differential wheel, and M is the diameter of the differential wheel;
Step 7: the wheel speed V L (k+1) fed back by the left differential wheel of the AGV at the moment k+1 and the wheel speed V R (k+1) fed back by the right differential wheel are fed back by the double-wheel differential driving motor, so that the centroid angular speed w (k+1) and the centroid speed V (k+1) of the AGV at the moment k+1 are calculated by using the formula (3):
Step 8: establishing a motion equation of the AGV according to the formula (4), and obtaining a centroid pose X (k+1) = (X k+1,yk+1,θk+1)T) of the AGV at the moment k+1:
In the formula (4), X (k) = (X k,yk,θk)T is the centroid pose of the AGV at the k moment, D (k) is the displacement of the AGV on a straight line in the unit sampling time interval of the k moment and the k+1 moment, and D (k) = v (k) ×Δt, delta (k) is the angular displacement of the AGV in the unit sampling time of the k moment and the k+1 moment, and delta (k) = w (k) ×Δt;
Step 9: after k is assigned to k, returning to the step 3 until the position coordinate at the current moment reaches the target position.
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