CN113985895B - AGV path tracking method based on optimization - Google Patents
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- 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
- G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- 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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Abstract
The invention discloses an optimal AGV path tracking method, wherein each path point comprises the position of the current point and the expected yaw angle of the point, the expected yaw angle is the tangential angle of the curve where the path point is located, the current closest point of the pose of the AGV is calculated, and finally the corresponding path length is calculated according to the running speed and the target time of the AGV, and all the path points from the closest point to the path length are output. According to the invention, the transverse control law of the vehicle is adjusted on line in real time by using an optimization tool according to the path and the vehicle running speed factors, so that the accurate control on path tracking and the robustness on running speed change are realized; the method mainly relates to the field of AGVs, and mainly aims to improve the accuracy of AGV path tracking in links such as logistics transportation and production, improve the robustness of transverse control on path change and the robustness on longitudinal speed change of a vehicle, and meanwhile, the online optimization strategy can be adjusted according to actual conditions, so that the optimal control effect can be achieved.
Description
Technical Field
The invention relates to the technical field of logistics, in particular to an AGV path tracking method based on optimization.
Background
In the field of production logistics and storage logistics, due to rising of labor cost and rapid development of robot technology, an AGV gradually becomes a trend, and the AGV integrates technologies such as positioning, sensing, navigation and control, wherein a path tracking technology belongs to a basic and important technology, a control method based on a pre-aiming point is generally adopted in a traditional path tracking technology, the pre-aiming distance is usually fixed or according to running speed change, the tracking path of the AGV is usually straight line, circular arc, bezier curve and the like, and the tracking effect of a traditional method on the curve is usually poor due to the fact that the pre-aiming distance does not consider the path change.
Disclosure of Invention
The invention aims to provide an AGV path tracking method based on optimization so as to solve the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions: the path tracking method based on the optimized AGV comprises the following steps:
A. path discretization is the path point: each path point comprises the position of the current point and the expected yaw angle of the point, wherein the expected yaw angle is the tangential angle of the curve where the path point is located, the current closest point of the pose where the AGV is located is calculated, the corresponding optimal path length is calculated according to the running speed and the target time of the AGV, and all path points from the closest point to the optimal path length are output;
B. Optimizing an AGV course angle: and then, calculating a value range of an AGV course angle to be determined according to the angular speed limit and the angular acceleration limit of the AGV course, and finally, solving an optimization problem according to the performance index and the limiting condition, thereby obtaining the optimal course of the path tracking, wherein the optimization problem is as follows: wherein θ is the AGV course angle to be confirmed; n is the number of path points; d i is the shortest distance from the ith path point to the running path of the vehicle when the course angle of the AGV is theta; θ i is the tangential angle of the curve where the i-th path point is located; θ min and θ max are the upper and lower bounds of the AGV heading angle constraint; w 1 and W 2 are the weights taken up by the distance error and heading error, respectively;
C. Heading control: firstly, estimating equivalent interference and angular velocity values of a controlled object by using a first-order linear extended state observer, wherein the input of the extended state observer is input u of the controlled object, u represents a command course angle at the last moment and output y of the controlled object, and y represents the actual angular velocity; and designing a PD control law according to the angular speed, the actual course angle and the expected course angle which are observed by the extended state observer, and finally obtaining the current expected course angle according to the uncertainty of the equivalent disturbance feedforward compensation system which is observed by the extended state observer.
The formula is as follows:
l 1 and l 2 are parameters of the extended state observer, y is the actual angular velocity, u is the control quantity, z 1 is the angular velocity estimate, and z 2 is the disturbance estimate.
Preferably, the path points and the current position are generated according to the path, and the performance index is designed according to the course angle of the AGV to be determined.
Preferably, according to the AGV command course angle optimally output, the course control outputs the command angular speed of the AGV chassis, and aims at the problem that the characteristics of the AGV load are different in different course angles, and the control algorithm is designed to achieve tracking and interference suppression functions of the command course angle by adopting ADRC so as to achieve accurate control.
Compared with the prior art, the invention has the following beneficial effects:
1. According to the invention, the transverse control law of the vehicle is adjusted on line in real time by using an optimization tool according to the path and the vehicle running speed factors, so that the accurate control on path tracking and the robustness on running speed change are realized; the method mainly relates to the field of AGVs, and mainly aims to improve the accuracy of AGV path tracking in links such as logistics transportation and production, improve the robustness of transverse control on path change and the robustness on longitudinal speed change of a vehicle, and meanwhile, the online optimization strategy can be adjusted according to actual conditions, so that the optimal control effect can be achieved.
Drawings
FIG. 1 is a flow chart of the path-following optimization of the present invention;
FIG. 2 is a block diagram of a control module according to the present invention.
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. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present document, it should be understood that the terms "center," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate or are based on the orientation or positional relationship shown in the drawings, merely to facilitate description of the present patent and simplify description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operate in a particular orientation, and thus should not be construed as limiting the present patent. In the description of the present document, it should be noted that, unless explicitly stated and limited otherwise, the terms "mounted," "connected," and "disposed" are to be construed broadly, and may be, for example, fixedly connected, disposed, detachably connected, disposed, or integrally connected and disposed. The specific meaning of the terms in this patent will be understood by those of ordinary skill in the art as the case may be.
Referring to fig. 1-2, an optimization-based AGV path tracking method includes the steps of:
A. Path discretization is the path point: each path point comprises the position of the current point and the expected yaw angle of the point, wherein the expected yaw angle is the tangential angle of the curve of the path point, the current closest point of the pose of the AGV is calculated, the corresponding optimal path length is calculated according to the running speed and the target time of the AGV, all path points from the closest point to the optimal path length are output, the straight line and the circular arc curve are uniformly written into the form of a Bezier curve so that all paths are kept consistent in a mathematical form, and the paths are discretized into the path points;
B. Optimizing an AGV course angle: and then, calculating a value range of an AGV course angle to be determined according to the angular speed limit and the angular acceleration limit of the AGV course, and finally, solving an optimization problem according to the performance index and the limiting condition, thereby obtaining the optimal course of the path tracking, wherein the optimization problem is as follows: wherein θ is the AGV course angle to be confirmed; n is the number of path points; d i is the shortest distance from the ith path point to the running path of the vehicle when the course angle of the AGV is theta; θ i is the tangential angle of the curve where the i-th path point is located; θ min and θ max are the upper and lower bounds of the AGV heading angle constraint; w 1 and W 2 are the weights taken up by the distance error and heading error, respectively;
C. Heading control: firstly, estimating equivalent interference and angular velocity values of a controlled object by using a first-order linear extended state observer, wherein the input of the extended state observer is input u of the controlled object, u represents a command course angle at the last moment and output y of the controlled object, and y represents the actual angular velocity; and designing a PD control law according to the angular speed, the actual course angle and the expected course angle which are observed by the extended state observer, and finally obtaining the current expected course angle according to the uncertainty of the equivalent disturbance feedforward compensation system which is observed by the extended state observer.
The formula is as follows:
l 1 and l 2 are parameters of the extended state observer, y is the actual angular velocity, u is the control quantity, z 1 is the angular velocity estimate, and z 2 is the disturbance estimate.
Embodiment one:
the path tracking method based on the optimized AGV comprises the following steps:
A. Path discretization is the path point: each path point comprises the position of the current point and the expected yaw angle of the point, wherein the expected yaw angle is the tangential angle of the curve of the path point, the current closest point of the pose of the AGV is calculated, the corresponding optimal path length is calculated according to the running speed and the target time of the AGV, all path points from the closest point to the optimal path length are output, the straight line and the circular arc curve are uniformly written into the form of a Bezier curve so that all paths are kept consistent in a mathematical form, and the paths are discretized into the path points;
B. Optimizing an AGV course angle: and then, calculating a value range of an AGV course angle to be determined according to the angular speed limit and the angular acceleration limit of the AGV course, and finally, solving an optimization problem according to the performance index and the limiting condition, thereby obtaining the optimal course of the path tracking, wherein the optimization problem is as follows: wherein θ is the AGV course angle to be confirmed; n is the number of path points; d i is the shortest distance from the ith path point to the running path of the vehicle when the course angle of the AGV is theta; θ i is the tangential angle of the curve where the i-th path point is located; θ min and θ max are the upper and lower bounds of the AGV heading angle constraint; w 1 and W 2 are the weights taken up by the distance error and heading error, respectively;
C. Heading control: firstly, estimating equivalent interference and angular velocity values of a controlled object by using a first-order linear extended state observer, wherein the input of the extended state observer is input u of the controlled object, u represents a command course angle at the last moment and output y of the controlled object, and y represents the actual angular velocity; and designing a PD control law according to the angular speed, the actual course angle and the expected course angle which are observed by the extended state observer, and finally obtaining the current expected course angle according to the uncertainty of the equivalent disturbance feedforward compensation system which is observed by the extended state observer.
The formula is as follows:
l 1 and l 2 are parameters of the extended state observer, y is the actual angular velocity, u is the control quantity, z 1 is the angular velocity estimate, and z 2 is the disturbance estimate.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (3)
1. An AGV path tracking method based on optimization is characterized in that: the path tracking method comprises the following steps:
A. Path discretization is the path point: each path point comprises the position of the current point and the expected yaw angle of the point, wherein the expected yaw angle is the tangential angle of the curve of the path point, the current closest point of the pose of the AGV is calculated, the corresponding optimal path length is calculated according to the running speed and the target time of the AGV, all path points from the closest point to the optimal path length are output, the straight line and the circular arc curve are uniformly written into the form of a Bezier curve so that all paths are kept consistent in a mathematical form, and the paths are discretized into the path points;
B. Optimizing an AGV course angle: and then, calculating a value range of an AGV course angle to be determined according to the angular speed limit and the angular acceleration limit of the AGV course, and finally, solving an optimization problem according to the performance index and the limiting condition, thereby obtaining the optimal course of the path tracking, wherein the optimization problem is as follows: wherein θ is the AGV course angle to be confirmed; n is the number of path points; d i is the shortest distance from the ith path point to the running path of the vehicle when the course angle of the AGV is theta; θ i is the tangential angle of the curve where the i-th path point is located; θ min and θ max are the upper and lower bounds of the AGV heading angle constraint; w 1 and W 2 are the weights taken up by the distance error and heading error, respectively;
C. heading control: firstly, estimating equivalent interference and angular velocity values of a controlled object by using a first-order linear extended state observer, wherein the input of the extended state observer is input u of the controlled object, u represents a command course angle at the last moment and output y of the controlled object, and y represents the actual angular velocity; then designing a PD control law according to the angular speed, the actual course angle and the expected course angle observed by the extended state observer, and finally obtaining the current expected course angle according to the uncertainty of the equivalent disturbance feedforward compensation system observed by the extended state observer;
The formula is as follows:
l 1 and l 2 are parameters of the extended state observer, y is the actual angular velocity, u is the control quantity, z 1 is the angular velocity estimate, and z 2 is the disturbance estimate.
2. The method of claim 1, wherein the method is characterized by: and generating path points and current positions according to the paths, and designing performance indexes of the AGV course angle to be determined.
3. The method of claim 1, wherein the method is characterized by: according to the optimally output AGV command course angle, the course control outputs the command angular velocity of the AGV chassis, and aims at the problem that the characteristics of the AGV load are different in different course angles, and the control algorithm is designed to achieve the tracking and interference suppression functions of the command course angle by adopting ADRC so as to achieve accurate control.
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