CN112987719A - Control method based on accurate tracking and multi-branch path AGV - Google Patents
Control method based on accurate tracking and multi-branch path AGV Download PDFInfo
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0234—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons
- G05D1/0236—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons in combination with a laser
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
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- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
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Abstract
The invention discloses a control method based on accurate tracking and multi-branch path AGV, which comprises the steps of constructing a four-wheel drive AGV kinematics model with independent steering; an elite guiding type optimization strategy is introduced, and parameters of the controller are optimized to realize the optimization and function realization of the system; the synchronous realization of image information processing and two-dimensional code reading is completed by adopting an integrated design scheme of visual information and code reading technology; by a system calibration method combining static setting and dynamic compensation, the error of a visual system is accurately eliminated; removing the influence of non-uniform illumination by a normalization method based on average irradiance; the image enhancement is carried out by directional color compensation and bilateral filtering, so that the robustness of the feature extraction of the guide path of the selected color ribbon is improved; the method aims at the actual requirements of engineering application, realizes and perfects the functions of the designed AGV, and realizes the development of functions of omnidirectional movement, multi-branch path identification and planning, autonomous obstacle avoidance, autonomous charging and the like of the AGV by means of omnidirectional vision guidance.
Description
Technical Field
The invention belongs to the technical field of intelligent equipment control, and particularly relates to a control method based on accurate tracking and multi-branch path AGV.
Background
An Automatic Guided Vehicle (AGV) is a wheeled mobile robot equipped with an electromagnetic or optical automatic guide device and capable of traveling along a predetermined path, and is widely used for material transportation in the fields of Automated production, intelligent storage and the like. The first automated guided vehicles were developed in the 50's of the 20 th century by Barrett electronics in the united states.
The AGV is a product under the development of high and new technologies, shows the influence of science and technology on the production capacity, greatly promotes the promotion and innovation of the modern manufacturing industry, and enables the modern manufacturing industry to gradually form the state of informatization, greening, automation, integration and high-degree industry fusion.
Disclosure of Invention
In view of the above, in order to solve the above-mentioned deficiencies of the prior art, the present invention provides a method for controlling an AGV based on accurate tracking and multiple branch paths, which uses an AGV cart based on an elite guidance control algorithm and an elite guidance mechanism based on multi-objective decision preference, and can effectively solve the problem of parameter optimization of a PID controller; the omnidirectional visual guidance AGV has the advantages of omnidirectional motion, multi-branch path identification and planning.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a control method based on accurate tracking and multi-branch path AGV is characterized in that: the method comprises the following steps:
s1: setting the rising time, the adjusting time and the IAE type error index as multiple targets, setting an elite judgment condition according to the control requirement of path tracking, namely decision preference, and keeping the diversity of individuals by using a lossless finite precision method II;
s2: sorting the optimal solutions of elite and Pareto according to the multi-target normalized incremental distance and the multi-target aggregation function, and calculating the individual copy probability by a normalized geometric ranking function according to the sorting level;
s3: constructing a four-wheel drive independent steering AGV kinematics model:
s31: establishing a global coordinate system XIOIRI and a local coordinate system XrOrYr fixed on an AGV body by taking the working space of the AGV as a plane; wherein, Or is the mass center of the AGV moving in all directions;
s32: in order to make the four wheels completely satisfy the ackermann geometry principle when turning independently, the steering angle when turning the four wheels satisfies the following relationship:
according to the relation among the variables, the relation among the turning angles is further obtained as the following formula (2):
the relationship between the running speeds of the inner and outer wheels is as follows (3):
s4: constructing an AGVS path topological structure model: the AGVS path topological structure model is constructed by the bidirectional path and path branch nodes such as L-shaped, T-shaped, cross-shaped and r-shaped.
Further, the step S32 further includes the following step S33: and (d, vd) is set as the pixel point after the actual pixel point (u, v) is subjected to image radial distortion correction, and in the camera internal parameter model of the AGV trolley, k1 and k2 are amplification coefficients of the pixel in the direction relative to the physical coordinate of the imaging plane, so that the formula (4) can be obtained:
the model parameters to be solved include the camera internal parameters u0, v0, kx and ky, the distortion parameters k1 and k2 and the external parameters R, T, which is a nonlinear optimization problem; m images with N grid intersections are collected, model parameters are optimized by adopting a maximum likelihood estimation method, and the optimal solution of the system can be obtained.
Further, the step S33 is followed by the step S34: the corrected imaging model can be simplified as follows:
and Apix is a scale factor of the pixel relative to the calibration template.
Further, the step S34 is followed by the step S35: let the coordinates of the control center point C in the distortion corrected image be (xc, yc), then:
where ψ, xc and yc are the rotation angle and the two translation components of the corrected AGV image coordinate system, respectively. By solving psi, xc and yc, the parameters of the corrected image relative to the AGV coordinate system can be obtained.
Furthermore, the elite guiding AGV controller of the control method comprises a motion controller and a dynamic controller, wherein the motion controller is connected with the dynamic controller.
The invention has the beneficial effects that:
the method is based on a data driving method, and an AGV kinematics model with four-wheel drive independent steering is constructed; on the basis, an elite guiding type optimization strategy is introduced, and parameters of the controller are optimized to realize the optimization and function realization of the system; the synchronous realization of image information processing and two-dimensional code reading is completed by adopting an integrated design scheme of visual information and code reading technology; by a system calibration method combining static setting and dynamic compensation, the error of a visual system is accurately eliminated; removing the influence of non-uniform illumination by a normalization method based on average irradiance; the image enhancement is carried out by directional color compensation and bilateral filtering, so that the robustness of the feature extraction of the guide path of the selected color ribbon is improved; the method aims at the actual requirements of engineering application, realizes and perfects the functions of the designed AGV, and realizes the development of functions of omnidirectional movement, multi-branch path identification and planning, autonomous obstacle avoidance, autonomous charging and the like of the AGV by means of omnidirectional vision guidance.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of an Elite guided AGV controller;
FIG. 2 is a schematic diagram of a kinematic model of a four-wheel drive independent steering AGV;
FIG. 3 is a schematic diagram of the output result of a camera before distortion correction;
fig. 4 is a schematic diagram of an output result of the camera after distortion correction.
Detailed Description
The following specific examples are given to further clarify, complete and detailed the technical solution of the present invention. The present embodiment is a preferred embodiment based on the technical solution of the present invention, but the scope of the present invention is not limited to the following embodiments.
A control method based on accurate tracking and multi-branch path AGV is characterized in that: the method comprises the following steps:
parameter setting is considered from the optimization perspective, and the parameter optimization problem of the PID controller can be effectively solved based on an elite guiding mechanism with multi-objective decision preference;
s1: setting the rising time, the adjusting time and the IAE type error index as multiple targets, setting an elite judgment condition according to the control requirement of path tracking, namely decision preference, and keeping the diversity of individuals by using a lossless finite precision method II;
s2: sorting the optimal solutions of elite and Pareto according to the multi-target normalized incremental distance and the multi-target aggregation function, and calculating the individual copy probability by a normalized geometric ranking function according to the sorting level; the NSGA-II optimized servo controller has high response speed and transition speed and small overshoot, and can be matched with the pose deviation rectifying capability of a path tracking algorithm;
s3: constructing a four-wheel drive independent steering AGV kinematics model:
s31: establishing a global coordinate system XIOIRI and a local coordinate system XrOrYr fixed on an AGV body by taking the working space of the AGV as a plane; wherein, Or is the mass center of the AGV moving in all directions;
s32: in order to make the four wheels completely satisfy the ackermann geometry principle when turning independently, the steering angle when turning the four wheels satisfies the following relationship:
according to the relation among the variables, the relation among the turning angles is further obtained as the following formula (2):
the relationship between the running speeds of the inner and outer wheels is as follows (3):
s4: constructing an AGVS path topological structure model: the AGVS path topological structure model is constructed by the bidirectional path and path branch nodes such as L-shaped, T-shaped, cross-shaped and r-shaped.
Because the AGV can only do two-dimensional rigid motion on the ground, no matter what motion mode the AGV does, the ground reference point is in one plane, and sufficient constraint cannot be obtained to solve all internal parameters. The actual pose of the camera has three angle errors and two translation errors relative to the ideal pose, and the final imaging may have tilt distortion, proportional distortion and radial distortion according to the imaging principle of the camera, so that accurate calibration is required to be performed in order to reduce the error between the output result and the actual value;
further, the step S32 further includes the following step S33: and (d, vd) is set as the pixel point after the actual pixel point (u, v) is subjected to image radial distortion correction, and in the camera internal parameter model of the AGV trolley, k1 and k2 are amplification coefficients of the pixel in the direction relative to the physical coordinate of the imaging plane, so that the formula (4) can be obtained:
the model parameters to be solved include the camera internal parameters u0, v0, kx and ky, the distortion parameters k1 and k2 and the external parameters R, T, which is a nonlinear optimization problem; m images with N grid intersections are collected, model parameters are optimized by adopting a maximum likelihood estimation method, and the optimal solution of the system can be obtained.
Further, the step S33 is followed by the step S34: the corrected imaging model can be simplified as follows:
and Apix is a scale factor of the pixel relative to the calibration template.
Further, the step S34 is followed by the step S35: let the coordinates of the control center point C in the distortion corrected image be (xc, yc), then:
where ψ, xc and yc are the rotation angle and the two translation components of the corrected AGV image coordinate system, respectively. By solving psi, xc and yc, the parameters of the corrected image relative to the AGV coordinate system can be obtained. The output results of the cameras before and after correction are shown in fig. 3 and 4.
Furthermore, the elite guiding AGV controller of the control method comprises a motion controller and a dynamic controller, wherein the motion controller is connected with the dynamic controller.
Further, in step S4, the features extracted from the original image have both strong representation capability for branch path pattern recognition and high accuracy for path model estimation, and the above requirements can be better satisfied by using a region area row and column projection and four-side boundary contour scanning simultaneous extraction method. Scanning the jth line of the N rows and M columns of binary image from left to right, wherein the first 1 and the last 1 are respectively recorded as hlj and hrj, and the number of 1 is recorded as hpj:
scanning the ith column from top to bottom, the first 1 and the last 1 are respectively denoted vti and vbi, and the number of 1 is denoted vpi, as follows:
the feature point sets of the four-boundary contour scanning based on the vector diagram model estimation are respectively
Hl＝{(x，y)|x＝hlj，y＝j，j＝1，2…N}
Hr＝{(x，y)|x＝hrj，y＝j，j＝1，2…N}
Vt＝{(x，y)|x＝i，y＝vti，i＝1，2…M}
Vb＝{(x，y)|x＝i，y＝vbi，i＝1，2…M) (9)；
The projection vectors of the path region features in the row direction and the column direction are respectively marked as Hp and Vp, and then
Hp＝[hp1…hpN]
Vp＝[vp1…vpN] (10)；
Hp and Vp are two linear spaces of the area of the path region for multi-branch path pattern recognition. Because the AGV has the characteristic of bidirectional movement, the DSP can obtain the current movement direction of the AGV through communication with the movement controller. One of the directions is defined as forward motion, and when the motion is reversed, all components of the vectors Hp and Vp are arranged in a reverse order, so that the same path feature description as the forward direction can be obtained.
In conclusion, the AGV control method based on accurate tracking and multi-branch path provided by the invention adopts the AGV trolley based on the elite guiding control algorithm and the elite guiding mechanism based on multi-target decision preference, so that the parameter optimization problem of the PID controller can be effectively solved; the method is based on a data driving method, and an AGV kinematics model with four-wheel drive independent steering is constructed; on the basis, an elite guiding type optimization strategy is introduced, and parameters of the controller are optimized to realize the optimization and function realization of the system; the synchronous realization of image information processing and two-dimensional code reading is completed by adopting an integrated design scheme of visual information and code reading technology; by a system calibration method combining static setting and dynamic compensation, the error of a visual system is accurately eliminated; removing the influence of non-uniform illumination by a normalization method based on average irradiance; the image enhancement is carried out by directional color compensation and bilateral filtering, so that the robustness of the feature extraction of the guide path of the selected color ribbon is improved; the method aims at the actual requirements of engineering application, realizes and perfects the functions of the designed AGV, and realizes the development of functions of omnidirectional movement, multi-branch path identification and planning, autonomous obstacle avoidance, autonomous charging and the like of the AGV by means of omnidirectional vision guidance.
The principal features, principles and advantages of the invention have been shown and described above. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to explain the principles of the invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the invention as expressed in the following claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (5)
1. A control method based on accurate tracking and multi-branch path AGV is characterized in that: the method comprises the following steps:
s1: setting the rising time, the adjusting time and the IAE type error index as multiple targets, setting an elite judgment condition according to the control requirement of path tracking, namely decision preference, and keeping the diversity of individuals by using a lossless finite precision method II;
s2: sorting the optimal solutions of elite and Pareto according to the multi-target normalized incremental distance and the multi-target aggregation function, and calculating the individual copy probability by a normalized geometric ranking function according to the sorting level;
s3: constructing a four-wheel drive independent steering AGV kinematics model:
s31: establishing a global coordinate system XIOIRI and a local coordinate system XrOrYr fixed on an AGV body by taking the working space of the AGV as a plane; wherein, Or is the mass center of the AGV moving in all directions;
s32: in order to make the four wheels completely satisfy the ackermann geometry principle when turning independently, the steering angle when turning the four wheels satisfies the following relationship:
according to the relation among the variables, the relation among the turning angles is further obtained as the following formula (2):
the relationship between the running speeds of the inner and outer wheels is as follows (3):
s4: constructing an AGVS path topological structure model: the AGVS path topological structure model is constructed by the bidirectional path and path branch nodes such as L-shaped, T-shaped, cross-shaped and r-shaped.
2. The AGV control method according to claim 1, wherein said AGV control method comprises: the step S32 further includes the following step S33: and (d, vd) is set as the pixel point after the actual pixel point (u, v) is subjected to image radial distortion correction, and in the camera internal parameter model of the AGV trolley, k1 and k2 are amplification coefficients of the pixel in the direction relative to the physical coordinate of the imaging plane, so that the formula (4) can be obtained:
the model parameters to be solved include the camera internal parameters u0, v0, kx and ky, the distortion parameters k1 and k2 and the external parameters R, T, which is a nonlinear optimization problem; m images with N grid intersections are collected, model parameters are optimized by adopting a maximum likelihood estimation method, and the optimal solution of the system can be obtained.
3. The AGV control method according to claim 2, wherein said AGV control method comprises: the step S33 is followed by a step S34: the corrected imaging model can be simplified as follows:
and Apix is a scale factor of the pixel relative to the calibration template.
4. The AGV control method according to claim 3, wherein said AGV control method further comprises: the step S34 is followed by a step S35: let the coordinates of the control center point C in the distortion corrected image be (xc, yc), then:
where ψ, xc and yc are the rotation angle and the two translation components of the corrected AGV image coordinate system, respectively. By solving psi, xc and yc, the parameters of the corrected image relative to the AGV coordinate system can be obtained.
5. The AGV control method according to claim 1, wherein said AGV control method comprises: the elite guiding AGV controller of the control method comprises a motion controller and a dynamic controller, wherein the motion controller is connected with the dynamic controller.
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