CN114510062A - Shuttle car navigation control method and system - Google Patents

Shuttle car navigation control method and system Download PDF

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Publication number
CN114510062A
CN114510062A CN202210308612.1A CN202210308612A CN114510062A CN 114510062 A CN114510062 A CN 114510062A CN 202210308612 A CN202210308612 A CN 202210308612A CN 114510062 A CN114510062 A CN 114510062A
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shuttle
task
acceleration
speed
ant
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CN114510062B (en
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林立峰
郭东进
袁绪龙
张波
袁绪彬
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Shandong Ximanke Technology Co ltd
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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
    • 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
    • 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
    • G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle

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  • Aviation & Aerospace Engineering (AREA)
  • Radar, Positioning & Navigation (AREA)
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  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Navigation (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)

Abstract

The invention belongs to the technical field of shuttle vehicles, and particularly discloses a shuttle vehicle navigation control method and a system. By adopting the technical scheme, the objective function is established, the shortest operation time and the minimum required number of the four-way shuttles are ensured, the cost is saved, and the problem of unstable system operation under the condition of high acceleration is solved.

Description

Shuttle car navigation control method and system
Technical Field
The invention belongs to the technical field of shuttle vehicles, and relates to a shuttle vehicle navigation control method and system.
Background
Along with the expansion of production scale and the shortage of land resources, the application of the dense storage warehouse in the market is more and more extensive, the dense storage warehouse is based on a dense goods shelf, has the characteristics of high density and high sealing performance, and the operation of entering and exiting goods is completed by means of a shuttle car which reciprocates in the dense goods shelf.
The shuttle vehicle control technology applied to the dense storage system in the domestic market at present is not complete enough, and is particularly reflected in the aspect of speed control. The length of the dense goods shelf track is relatively short, so that the acceleration of the shuttle vehicle in the operation of the goods shelf roadway directly determines the operation efficiency of the system, however, under the condition of traditional uniform acceleration speed control, the increase of the acceleration brings certain influence on the stability of goods, and the system is not stable enough in the operation under the condition of high acceleration.
Disclosure of Invention
The invention aims to provide a shuttle vehicle navigation control method and system, which solve the problem of unstable system operation under the condition of high acceleration.
In order to achieve the purpose, the basic scheme of the invention is a shuttle car navigation control method, which comprises the following steps:
acquiring position information and speed information of a plurality of four-way shuttles;
establishing an objective function based on the position information and the speed information, and setting constraint conditions, wherein the constraint conditions comprise elevator constraint and sequencing constraint;
and solving the objective function to generate a task execution plan of a plurality of four-way shuttles, obtaining the optimal solution output and controlling the shuttles.
The working principle and the beneficial effects of the basic scheme are as follows: the scheme utilizes the position information and the speed information to generate a subsequent required task execution plan and establish a target function. And carrying out optimization solution on the target welding by using the constraint conditions to obtain the optimal solution output and control the shuttle car, thereby realizing automatic navigation control on the shuttle car and ensuring the stable operation of the shuttle car under the control of the optimal solution.
Further, the established objective function is:
and establishing a multi-objective function by minimizing the running time and the acceleration energy:
Figure 438128DEST_PATH_IMAGE001
wherein the maximum value of the running time
Figure 474217DEST_PATH_IMAGE002
(ii) a Maximum value of energy loss
Figure 38054DEST_PATH_IMAGE003
(ii) a I is a shuttle index, I is the total number of shuttles, I =1,2,3 … … I; j is the task index, J is the total number of tasks, J =1,2,3 … … J;
Figure 425173DEST_PATH_IMAGE004
the execution time of the shuttle vehicle i in the task j is;
Figure 467078DEST_PATH_IMAGE005
is the stop time at task j for shuttle i, including the time to get in and get out of stock;
Figure 59471DEST_PATH_IMAGE006
for the weight of the transport cargo of shuttle i at task j,
Figure 856526DEST_PATH_IMAGE007
is the maximum speed of shuttle i during the transport of task j.
And an objective function is established, so that the shortest operation time and the minimum required number of four-way shuttles are ensured, and the cost is saved.
Further, the velocity is calculated
Figure 403045DEST_PATH_IMAGE007
During the process, each four-way shuttle vehicle is subjected to variable acceleration control, the time required by the straight-going stage is ensured to be as little as possible, the speeds at the starting point, the corner and the end point are zero, and the control is carried out between two points with the zero speed:
the running time between two points with the speed being zero is divided into 4 sections, namely a 0-t1 section, a t1-t2 section, a t2-t3 section and a t3-t4 section;
0-t1 plus acceleration phase: gradually accelerates, and the speed is increased from 0 to
Figure 514220DEST_PATH_IMAGE008
And the acceleration is gradually increased, the jerk is
Figure 524902DEST_PATH_IMAGE009
；
t1-t2 deceleration and acceleration phases: gradually accelerate at a speed of
Figure 430541DEST_PATH_IMAGE008
Increase to
Figure 526673DEST_PATH_IMAGE010
And the acceleration is gradually decreased until the acceleration is zero, the jerk is:
Figure 408916DEST_PATH_IMAGE011
t2-t3 acceleration and deceleration stage: gradually reduce the speed from
Figure 477366DEST_PATH_IMAGE010
Reduced to
Figure 616223DEST_PATH_IMAGE008
And the acceleration gradually increases, the jerk being:
Figure 137334DEST_PATH_IMAGE012
t3-t4 deceleration phase: gradually reduce the speed from
Figure 387050DEST_PATH_IMAGE008
Decreasing to 0 and gradually decreasing acceleration, jerk being:
Figure 310007DEST_PATH_IMAGE013
and the distance S between two points with the speed of zero satisfies the following conditions:
Figure 619765DEST_PATH_IMAGE014
according to the distance of each task and the stability evaluation strategy, the fastest speed is determined
Figure 126708DEST_PATH_IMAGE010
And determining the task execution time by the objective function.
And the system stability is ensured on the basis of increasing the acceleration by adopting a variable acceleration speed control mode.
Further, during operation, the stability assessment strategy is:
the stability factor is:
Figure 117798DEST_PATH_IMAGE015
wherein,
Figure 957578DEST_PATH_IMAGE016
is the weight of the goods and is,
Figure 375921DEST_PATH_IMAGE017
in order to be the weight of the shuttle car,
Figure 606045DEST_PATH_IMAGE018
is the height of the cargo or cargo,
Figure 463142DEST_PATH_IMAGE019
the height of the shuttle car is the height of the shuttle car,
Figure 593647DEST_PATH_IMAGE020
in order to provide the shuttle with the area of the pallet,
Figure 245208DEST_PATH_IMAGE021
the contact area between the goods and the shuttle vehicle bearing tray is shown, a is the acceleration of the shuttle vehicle, f is the friction coefficient between the goods and the shuttle vehicle bearing tray, and g is the gravity acceleration;
if coefficient of stabilityNIf the threshold value is larger than the threshold value, the stability is better, and the acceleration can be continued;
if coefficient of stabilityNAnd if the speed is less than the threshold value, the acceleration is suspended, and the original speed is maintained.
And carrying out stability evaluation to further ensure the running stability of the shuttle.
Further, the method of setting the constraint condition is as follows:
and (3) restricting the elevator:
Figure 228208DEST_PATH_IMAGE022
wherein, K represents a set of elevators, K belongs to K, and K = { 1., nK };
Figure 561100DEST_PATH_IMAGE023
indicating that the shuttle i is at task j and utilizing the kth elevator;
ordering constraint:
the shuttle can be driven to the position of the next task only after the previous task finishes the goods exchange:
Figure 109893DEST_PATH_IMAGE024
wherein,
Figure 135618DEST_PATH_IMAGE025
the shuttle i finishes the operation time at task j;
Figure 402651DEST_PATH_IMAGE026
starting operation time of the shuttle vehicle i at task j + 1;
Figure 772191DEST_PATH_IMAGE027
is the transit time between task j and task j + 1;
Figure 175490DEST_PATH_IMAGE028
for the weight of the transport cargo of shuttle i at task j,
Figure 840958DEST_PATH_IMAGE029
is the maximum load of a shuttle vehicle.
And acquiring corresponding constraint conditions, solving the objective function and facilitating calculation.
Further, the method for generating the task execution plan of the shuttle vehicle comprises the following steps:
Figure 595287DEST_PATH_IMAGE030
distance to execute order j for shuttle i;
Figure 4403DEST_PATH_IMAGE031
for shuttle
Figure 229586DEST_PATH_IMAGE032
Prize of fulfillment order j equal to
Figure 659430DEST_PATH_IMAGE030
；
S1, initializing ant colony algorithm to generate multiple patrol ants, each of which is shuttle vehicle for executing, initializing all ants as successful ants, and making the bonus profit of each ant be the maximum distance that the shuttle vehicle can travel
Figure 307580DEST_PATH_IMAGE033
；
S2, if the termination condition is reached, executing step S6, if the termination condition is not reached, calculating the next feasible moving position of the ant, and selecting a task position every time the ant walks; if the ants finish the search, namely the construction of J tasks is finished, the bonus income acquired by the ants is calculated, the termination condition is that r ants finish the search, and r is less than or equal to the total number I of the vehicles passing through the lock;
s3, if the total bonus collected by an ant is less than the average bonus collected by the former ant, the search of the ant is considered to be successful, if the search of a certain ant is successful, the ant is used to update the average bonus, and the pheromone is updated;
s4, if the pheromone is used, making a decision on the next move, from p1Point trend p2The probability of a point is:
Figure 51545DEST_PATH_IMAGE034
wherein,
Figure 960595DEST_PATH_IMAGE035
is p1Point trend p2Probability of a point, p2Is an order p1The order that is available after execution,
Figure 702286DEST_PATH_IMAGE036
is derived from p for ants1Point trend p2A corresponding pheromone value in the pheromone table;
s5, if the ant completes the search, assigning a new task to the idle ant, returning to step S2;
and S6, outputting the task execution plan.
And generating a task execution plan by using an ant colony algorithm and using operation.
Further, the method of updating pheromones is as follows:
establishing an pheromone table, wherein the initial value of all values in the pheromone table is zero, and each time the pheromone needs to be updated, the pheromone is aimed at the current successful ants or ants
Figure 696787DEST_PATH_IMAGE037
Updating the corresponding pheromone of the order existing in the solution, and keeping other unrelated order pheromones unchanged;
Figure 742978DEST_PATH_IMAGE037
is the one with the smallest prize;
for bonus benefits are
Figure 647480DEST_PATH_IMAGE037
In the execution plan of
Figure 419127DEST_PATH_IMAGE036
Is equal to
Figure 838607DEST_PATH_IMAGE038
Wherein
Figure 127637DEST_PATH_IMAGE033
The maximum distance that the shuttle can travel;
for the execution plan of successful ants, let
Figure 745701DEST_PATH_IMAGE036
Is equal to
Figure 327729DEST_PATH_IMAGE039
And g is the maximum bonus gain.
And the pheromone is updated, the ant colony algorithm is ensured to be smoothly carried out, the operation is simple, and the use is facilitated.
Further, solving the objective function adopts a genetic algorithm, an ant colony algorithm, a particle swarm algorithm, a multi-objective optimization algorithm based on decomposition, or a differential evolution algorithm.
And selecting a proper algorithm according to the requirement, so that the method is convenient to use.
The invention also provides a shuttle car navigation control system which comprises a data acquisition module and a control module, wherein the data acquisition module is used for acquiring the position information and the speed information of a plurality of four-way shuttle cars, the output end of the data acquisition module is connected with the input end of the control module, the output end of the control module is connected with the control end of the shuttle car, and the control module executes the method to carry out the shuttle car navigation control.
The system establishes a target function, performs navigation control on the shuttle cars, ensures the operation time and the required number of the four-way shuttle cars, and saves the control cost. And meanwhile, the shuttle vehicle is controlled to optimally operate, so that unstable operation is avoided.
Drawings
FIG. 1 is a schematic flow diagram of a shuttle car navigation control method of the present invention;
fig. 2 is a schematic structural diagram of the operation process of the shuttle car navigation control method.
Reference numerals in the drawings of the specification include: the system comprises a shuttle vehicle longitudinal track 1, a shuttle vehicle 2, an idle goods space 3, a shuttle vehicle reversing node 4, a shuttle vehicle transverse track 5, a hoisting machine 6 and a handover buffer area 7.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, it is to be understood that the terms "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate orientations or positional relationships based on those shown in the drawings, and are used merely for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.
In the description of the present invention, unless otherwise specified and limited, it is to be noted that the terms "mounted," "connected," and "connected" are to be interpreted broadly, and may be, for example, a mechanical connection or an electrical connection, a communication between two elements, a direct connection, or an indirect connection via an intermediate medium, and specific meanings of the terms may be understood by those skilled in the art according to specific situations.
The invention discloses a shuttle car navigation control method, which solves the problem of unstable system operation under the condition of high acceleration. As shown in fig. 1 and 2, the shuttle car navigation control method in the present scheme includes the following steps:
the method comprises the steps that position information and speed information of a plurality of four-way shuttle cars are obtained, and the position information of each four-way shuttle car can be obtained by a positioning system carried by the shuttle car; the speed information can be obtained by a speed sensor arranged on the speed information acquisition device;
establishing an objective function based on the position information and the speed information, and setting constraint conditions, wherein the constraint conditions comprise elevator constraint and sequencing constraint;
and solving the objective function to generate a task execution plan of a plurality of four-way shuttles, obtaining Pareto (Pareto Optimality, also called Pareto efficiency, which is an ideal state of resource allocation) optimal solution output and controlling the shuttles. Solving the objective function by adopting a genetic algorithm, an ant colony algorithm, a particle swarm algorithm, a multi-objective optimization algorithm based on decomposition, a differential evolution algorithm and the like. The structure of the shuttle vehicle 2 in the running process of the shuttle vehicle navigation control method comprises a shuttle vehicle longitudinal rail 1, the shuttle vehicle 2, an idle goods space 3, a shuttle vehicle reversing node 4, a shuttle vehicle transverse rail 5, a lifter 6 and a handover buffer area 7.
In a preferred embodiment of the present invention, the established objective function is:
and establishing a multi-objective function by minimizing the running time and the acceleration energy:
Figure 968926DEST_PATH_IMAGE001
wherein the maximum value of the running time
Figure 920702DEST_PATH_IMAGE002
(ii) a Maximum value of energy loss
Figure 534217DEST_PATH_IMAGE003
(ii) a I is a shuttle index, I is the total number of shuttles, I =1,2,3 … … I; j is the task index, J is the total number of tasks, J =1,2,3 … … J;
Figure 850929DEST_PATH_IMAGE004
the execution time of the shuttle vehicle i in the task j is determined;
Figure 41739DEST_PATH_IMAGE005
is the stop time at task j for shuttle i, including the time to get in and get out of stock;
Figure 171106DEST_PATH_IMAGE006
for the weight of the transport cargo of shuttle i at task j,
Figure 701445DEST_PATH_IMAGE007
is the maximum speed of shuttle i during the transport of task j.
Calculating speed
Figure 516954DEST_PATH_IMAGE007
During the process, each four-way shuttle vehicle is subjected to variable acceleration control, the time required by the straight-going stage is ensured to be as little as possible, the speeds at the starting point, the corner and the end point are zero, and the control is carried out between two points with the zero speed:
the running time between two points with the speed being zero is divided into 4 sections, namely a 0-t1 section, a t1-t2 section, a t2-t3 section and a t3-t4 section; preferably, the time interval of each segment is the same, and
Figure 804847DEST_PATH_IMAGE040
；
0-t1 plus acceleration phase: gradually accelerates, and the speed is increased from 0 to
Figure 36108DEST_PATH_IMAGE008
And the acceleration is gradually increased, the jerk is
Figure 748849DEST_PATH_IMAGE009
；
t1-t2 deceleration and acceleration phases: gradually accelerate at a speed of
Figure 843582DEST_PATH_IMAGE008
Increase to
Figure 274563DEST_PATH_IMAGE010
And the acceleration is gradually decreased until the acceleration is zero, the jerk is:
Figure 43936DEST_PATH_IMAGE011
t2-t3 acceleration and deceleration stage: gradually reduce the speed from
Figure 486550DEST_PATH_IMAGE010
Reduced to
Figure 378283DEST_PATH_IMAGE008
And the acceleration gradually increases, the jerk being:
Figure 703085DEST_PATH_IMAGE012
t3-t4 deceleration phase: gradually reduce the speed from
Figure 977946DEST_PATH_IMAGE008
Decreasing to 0 and gradually decreasing acceleration, jerk being:
Figure 399700DEST_PATH_IMAGE013
and the distance S between two points with the speed of zero satisfies the following conditions:
Figure 603279DEST_PATH_IMAGE042
determining the fastest speed according to the distance of each task and the stability evaluation strategy
Figure 415378DEST_PATH_IMAGE010
And determining the task execution time by the objective function. Therefore, the shuttle vehicle is ensured to operate quickly and stably, the use is facilitated, and the working efficiency is accelerated.
In a preferred embodiment of the present invention, during the operation process, the stability evaluation strategy is:
the stability factor is:
Figure 854449DEST_PATH_IMAGE015
wherein,
Figure 6076DEST_PATH_IMAGE016
is the weight of the goods and is,
Figure 505190DEST_PATH_IMAGE017
in order to be the weight of the shuttle car,
Figure 326557DEST_PATH_IMAGE018
is the height of the cargo or cargo,
Figure 444686DEST_PATH_IMAGE019
the height of the shuttle car is the height of the shuttle car,
Figure 841032DEST_PATH_IMAGE020
in order to provide the shuttle with the area of the pallet,
Figure 386414DEST_PATH_IMAGE021
the contact area between the goods and the shuttle vehicle bearing tray is shown, a is the acceleration of the shuttle vehicle, f is the friction coefficient between the goods and the shuttle vehicle bearing tray, and g is the gravity acceleration;
if coefficient of stabilityNIf the value is larger than the threshold (the value can be preset by using experimental specific measurement, and if the value is set to 1), the stability is better, and the acceleration can be continued;
if coefficient of stabilityNAnd if the speed is less than the threshold value, the acceleration is suspended, and the original speed is maintained.
In a preferred embodiment of the present invention, the method for setting the constraint condition includes:
and (3) restricting the elevator:
Figure 907526DEST_PATH_IMAGE022
wherein, K represents a set of elevators, K belongs to K, and K = { 1., nK };
Figure 953979DEST_PATH_IMAGE023
indicating that the shuttle i is at task j and utilizing the kth elevator;
ordering constraint:
the shuttle can be driven to the position of the next task only after the previous task finishes the goods exchange:
Figure 578733DEST_PATH_IMAGE024
wherein,
Figure 419650DEST_PATH_IMAGE025
the shuttle i finishes the operation time at task j;
Figure 428057DEST_PATH_IMAGE026
starting operation time of the shuttle vehicle i at task j + 1;
Figure 887989DEST_PATH_IMAGE027
is the transit time between task j and task j + 1;
Figure 258927DEST_PATH_IMAGE028
for the weight of the transport cargo of shuttle i at task j,
Figure 880533DEST_PATH_IMAGE029
is the maximum load of a shuttle vehicle.
In a preferred embodiment of the present invention, the method for generating the task execution plan of the shuttle vehicle includes:
Figure 969711DEST_PATH_IMAGE030
distance to execute order j for shuttle i;
Figure 263027DEST_PATH_IMAGE031
for shuttle
Figure 629418DEST_PATH_IMAGE032
Prize for executing order j equal to
Figure 546558DEST_PATH_IMAGE030
；
S1, initializing ant colony algorithm to generate multiple patrol ants, each of which is shuttle vehicle for executing, initializing all ants as successful ants, and making the bonus profit of each ant be the maximum distance that the shuttle vehicle can travel
Figure 732820DEST_PATH_IMAGE033
；
S2, if the termination condition is reached, executing step S6, if the termination condition is not reached, calculating the next feasible moving position of the ant, and selecting a task position every time the ant walks; if the ants finish the search, the construction of J tasks is finished, the bonus income obtained by the ants is calculated, the termination condition is that r ants finish the search, and r is less than or equal to the total number I of the vehicles passing through the lock;
s3, if the total bonus collected by an ant is less than the average bonus collected by the former ant, the search of the ant is considered to be successful, if the search of a certain ant is successful, the ant is used to update the average bonus, and the pheromone is updated;
s4, if the pheromone is used, making a decision on the next move, from p1Point trend p2The probability of a point is:
Figure 331291DEST_PATH_IMAGE034
wherein,
Figure 676822DEST_PATH_IMAGE035
is p1Point trend p2Probability of a point, p2Is an order p1The order that is available after execution,
Figure 138765DEST_PATH_IMAGE036
is derived from p for ants1Point trend p2A corresponding pheromone value in the pheromone table;
s5, if the ant completes the search, assigning a new task to the idle ant, returning to step S2;
and S6, outputting the task execution plan. The termination condition is that a set number of tasks are performed or that the difference between the previous and next solutions is less than the error.
The method of updating pheromones is as follows:
establishing an pheromone table, wherein the initial value of all values in the pheromone table is zero, and each time the pheromone needs to be updated, the pheromone is aimed at the current successful ants or ants
Figure 936957DEST_PATH_IMAGE037
Updating the corresponding pheromone of the order existing in the solution, and keeping other unrelated order pheromones unchanged;
Figure 339119DEST_PATH_IMAGE037
is the one with the smallest prize;
for bonus benefits are
Figure 148944DEST_PATH_IMAGE037
In the execution plan of
Figure 345570DEST_PATH_IMAGE036
Is equal to
Figure 365478DEST_PATH_IMAGE038
Wherein
Figure 69867DEST_PATH_IMAGE033
The maximum distance that the shuttle can travel;
for the execution plan of successful ants, let
Figure 734198DEST_PATH_IMAGE036
Is equal to
Figure 429621DEST_PATH_IMAGE039
And g is the maximum bonus gain.
The invention also provides a shuttle car navigation control system which comprises a data acquisition module and a control module, wherein the data acquisition module is used for acquiring the position information and the speed information of a plurality of four-way shuttle cars, the output end of the data acquisition module is electrically connected with the input end of the control module, the output end of the control module is electrically connected with the control end of the shuttle car, and the control module executes the method to carry out the shuttle car navigation control.
The scheme establishes the objective function, ensures the shortest operation time and the minimum required number of the four-way shuttle vehicles, and saves the cost. And a variable acceleration speed control mode is adopted, and the stability of the system is ensured on the basis of increasing the acceleration.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims (9)

1. A shuttle car navigation control method is characterized by comprising the following steps:
acquiring position information and speed information of a plurality of four-way shuttles;
establishing an objective function based on the position information and the speed information, and setting constraint conditions, wherein the constraint conditions comprise elevator constraint and sequencing constraint;
and solving the objective function to generate a task execution plan of a plurality of four-way shuttles, obtaining the optimal solution output and controlling the shuttles.
2. The shuttle car navigation control method of claim 1, wherein the established objective function is:
and establishing a multi-objective function by minimizing the running time and the acceleration energy:
Figure 183926DEST_PATH_IMAGE001
wherein the maximum value of the running time
Figure 537284DEST_PATH_IMAGE002
(ii) a Maximum value of energy loss
Figure 317022DEST_PATH_IMAGE003
(ii) a I is a shuttle index, I is the total number of shuttles, I =1,2,3 … … I; j is the task index, J is the total number of tasks, J =1,2,3 … … J;
Figure 649914DEST_PATH_IMAGE004
the execution time of the shuttle vehicle i in the task j is;
Figure 464286DEST_PATH_IMAGE005
is the stop time at task j for shuttle i, including the time to get in and get out of stock;
Figure 224432DEST_PATH_IMAGE006
for the weight of the transport cargo of shuttle i at task j,
Figure 429148DEST_PATH_IMAGE007
is the maximum speed of shuttle i during the transport of task j.
3. The shuttle car navigation control method of claim 2, wherein the velocity is calculated
Figure 628048DEST_PATH_IMAGE007
During the process, each four-way shuttle vehicle is subjected to variable acceleration control, the time required by the straight-going stage is ensured to be as little as possible, the speeds at the starting point, the corner and the end point are zero, and the control is carried out between two points with the zero speed:
the running time between two points with the speed being zero is divided into 4 sections, namely a 0-t1 section, a t1-t2 section, a t2-t3 section and a t3-t4 section;
0-t1 plus acceleration phase: gradually accelerates, and the speed is increased from 0 to
Figure 733145DEST_PATH_IMAGE008
And the acceleration is gradually increased, the jerk is
Figure 664192DEST_PATH_IMAGE009
；
t1-t2 deceleration and acceleration phases: gradually accelerate at a speed of
Figure 418522DEST_PATH_IMAGE008
Increase to
Figure 93217DEST_PATH_IMAGE010
And the acceleration gradually decreases until the acceleration is zero, the jerk being:
Figure 616602DEST_PATH_IMAGE011
t2-t3 acceleration and deceleration stage: gradually reduce the speed from
Figure 984129DEST_PATH_IMAGE010
Reduced to
Figure 661973DEST_PATH_IMAGE008
And the acceleration gradually increases, the jerk being:
Figure 937097DEST_PATH_IMAGE012
t3-t4 deceleration phase: gradually reduce the speed from
Figure 518251DEST_PATH_IMAGE008
Decreasing to 0 and gradually decreasing acceleration, jerk being:
Figure 853417DEST_PATH_IMAGE013
and the distance S between two points with the speed of zero satisfies the following conditions:
Figure 520022DEST_PATH_IMAGE015
determining the fastest speed according to the distance of each task and the stability evaluation strategy
Figure 598836DEST_PATH_IMAGE010
And determining the task execution time by the objective function.
4. The shuttle car navigation control method of claim 3, wherein during operation, the stability assessment strategy is:
the stability factor is:
Figure 34497DEST_PATH_IMAGE016
wherein,
Figure 242362DEST_PATH_IMAGE017
is the weight of the goods and is,
Figure 193000DEST_PATH_IMAGE018
in order to be the weight of the shuttle car,
Figure 13189DEST_PATH_IMAGE019
is the height of the cargo or cargo,
Figure 303356DEST_PATH_IMAGE020
the height of the shuttle car is the height of the shuttle car,
Figure 245904DEST_PATH_IMAGE021
in order to provide the shuttle with the area of the pallet,
Figure 621522DEST_PATH_IMAGE022
the contact area between the goods and the shuttle vehicle bearing tray is shown, a is the acceleration of the shuttle vehicle, f is the friction coefficient between the goods and the shuttle vehicle bearing tray, and g is the gravity acceleration;
if coefficient of stabilityNIf the threshold value is larger than the threshold value, the stability is better, and the acceleration can be continued;
if coefficient of stabilityNAnd if the speed is less than the threshold value, the acceleration is suspended, and the original speed is maintained.
5. The shuttle car navigation control method according to claim 1, wherein the constraint condition is set by a method comprising:
and (3) restricting the elevator:
Figure 42139DEST_PATH_IMAGE023
wherein, K represents a set of elevators, K belongs to K, and K = { 1., nK };
Figure 950927DEST_PATH_IMAGE024
indicating that the shuttle i is at task j and utilizing the kth elevator;
ordering constraint:
the shuttle can be driven to the position of the next task only after the previous task finishes the goods exchange:
Figure 64376DEST_PATH_IMAGE025
wherein,
Figure 927290DEST_PATH_IMAGE026
the shuttle i finishes the operation time at task j;
Figure 89281DEST_PATH_IMAGE027
starting operation time of the shuttle vehicle i at task j + 1;
Figure 150778DEST_PATH_IMAGE028
is the transit time between task j and task j + 1;
Figure 372812DEST_PATH_IMAGE029
for the weight of the transport cargo of shuttle i at task j,
Figure 785339DEST_PATH_IMAGE030
is the maximum load of a shuttle vehicle.
6. The shuttle car navigation control method according to claim 1, wherein the method of generating the mission execution plan of the shuttle car is as follows:
Figure 249556DEST_PATH_IMAGE031
distance to execute order j for shuttle i;
Figure 368822DEST_PATH_IMAGE032
for shuttle
Figure 558494DEST_PATH_IMAGE033
Prize of fulfillment order j equal to
Figure 396000DEST_PATH_IMAGE031
；
S1, initializing ant colony algorithm to generate multiple patrol ants, each of which is shuttle vehicle for executing, initializing all ants as successful ants, and making the bonus profit of each ant be the maximum distance that the shuttle vehicle can travel
Figure 962111DEST_PATH_IMAGE034
；
S2, if the termination condition is reached, executing step S6, if the termination condition is not reached, calculating the next feasible moving position of the ant, and selecting a task position every time the ant walks; if the ants finish the search, namely the construction of J tasks is finished, the bonus income acquired by the ants is calculated, the termination condition is that r ants finish the search, and r is less than or equal to the total number I of the vehicles passing through the lock;
s3, if the total bonus collected by an ant is less than the average bonus collected by the former ant, the search of the ant is considered to be successful, if the search of a certain ant is successful, the ant is used to update the average bonus, and the pheromone is updated;
s4, if the pheromone is used, making a decision on the next move, from p1Point trend p2Probability of a point:
Figure 201462DEST_PATH_IMAGE035
wherein,
Figure 998255DEST_PATH_IMAGE036
is p1Point trend p2Probability of a point, p2Is an order p1The order that is available after execution,
Figure 385374DEST_PATH_IMAGE037
is derived from p for ants1Point trend p2A corresponding pheromone value in the pheromone table;
s5, if the ant completes the search, assigning a new task to the idle ant, returning to step S2;
and S6, outputting the task execution plan.
7. The shuttle car navigation control method of claim 6, wherein the method of updating the pheromone is as follows:
establishing pheromone table, where all values in the table are zero, and each time the pheromone needs to be updated, aiming at current successful ants or ants
Figure 692858DEST_PATH_IMAGE038
Updating the corresponding pheromone of the order existing in the solution, and keeping other unrelated order pheromones unchanged;
Figure 583454DEST_PATH_IMAGE038
is the one with the smallest prize;
for bonus benefits are
Figure 318192DEST_PATH_IMAGE038
In the execution plan of
Figure 927028DEST_PATH_IMAGE037
Is equal to
Figure 38203DEST_PATH_IMAGE039
Wherein
Figure 508540DEST_PATH_IMAGE034
The maximum distance that the shuttle can travel;
for the execution plan of successful ants, let
Figure 476496DEST_PATH_IMAGE037
Is equal to
Figure 510311DEST_PATH_IMAGE040
G is maximum prize payoutIt is beneficial to.
8. The shuttle car navigation control method according to claim 1, wherein solving the objective function employs a genetic algorithm, or an ant colony algorithm, or a particle swarm algorithm, or a decomposition-based multi-objective optimization algorithm, or a differential evolution algorithm.
9. A shuttle car navigation control system is characterized by comprising a data acquisition module and a control module, wherein the data acquisition module is used for acquiring position information and speed information of a plurality of four-way shuttle cars, the output end of the data acquisition module is connected with the input end of the control module, the output end of the control module is connected with the control end of the shuttle cars, and the control module executes the method of any one of claims 1 to 8 to conduct shuttle car navigation control.
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