CN114444828A - Multi-machine cooperative dynamic task allocation method for same agricultural machine - Google Patents

Multi-machine cooperative dynamic task allocation method for same agricultural machine Download PDF

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CN114444828A
CN114444828A CN202011202172.9A CN202011202172A CN114444828A CN 114444828 A CN114444828 A CN 114444828A CN 202011202172 A CN202011202172 A CN 202011202172A CN 114444828 A CN114444828 A CN 114444828A
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task
machine
agricultural
agricultural machine
cost
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王猛
赵博
刘阳春
苑严伟
伟利国
汪凤珠
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Chinese Academy of Agricultural Mechanization Sciences
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Abstract

A multi-machine cooperative dynamic task allocation method for the same kind of agricultural machine comprises the following steps: constructing a multi-machine cooperative cost function based on the performance of the agricultural machinery and the task parameters according to the multi-machine cooperative operation scene; constructing an agricultural machinery bidding cost function and a cluster cost function after bidding completion; constructing a multi-machine collaborative dynamic task allocation system based on a remote cloud service platform and a wireless ad hoc network; and when a new task needs to be distributed, the system distributes the new task by improving a contract network algorithm to finally obtain an optimal task distribution result. The invention solves the problem of how to reasonably and dynamically allocate tasks and task execution sequences under the condition that a new task is added or an agricultural machine is out of order in the operation process of a plurality of agricultural machines of the same kind in an agricultural machine cooperative society or farm.

Description

Multi-machine cooperative dynamic task allocation method for same agricultural machine
Technical Field
The invention relates to an agricultural machinery multi-machine cooperative work task allocation technology, in particular to a same agricultural machinery multi-machine cooperative dynamic task allocation method based on an improved contract network algorithm.
Background
With the development and popularization of agricultural machinery cooperative society and farm operation modes in China, the land and agricultural machinery show a concentrated trend, the most common operation scene is that tasks and sequences are firstly distributed to specified agricultural machinery before operation, and each agricultural machinery returns to a garage after completing respective operation task. The problem that a new task is added or the agricultural machine fails is frequently caused in the multi-machine cooperative operation process of the agricultural machine, and the task to be distributed is dynamically distributed effectively in real time, so that the operation cost can be effectively reduced, and the operation time can be shortened.
The common methods for solving the dynamic task allocation comprise: firstly, using a heuristic algorithm to redistribute uncompleted tasks through a remote service platform; and secondly, realizing the redistribution of the incomplete tasks through the bidding process among agricultural machinery by using a contract network algorithm. The first method belongs to centralized task allocation, a large amount of calculation is centralized to a server, the pressure on the server is high, and the allocation effect is good; the second method belongs to distributed task allocation, wherein the task allocation is completed by utilizing the computing power of an onboard computer of each agricultural machine and the mutual communication among the agricultural machines, the time consumption is short, no pressure is applied to a server, and the allocation effect is poor. In order to reduce the calculation amount of the server and the failure probability of the server, a method capable of fully utilizing the calculation capacity of an airborne computer to realize task allocation is urgently needed in the field.
Disclosure of Invention
The invention aims to solve the technical problem of providing a multi-machine cooperative dynamic task allocation method for the same kind of agricultural machinery based on an improved contract network algorithm.
In order to achieve the above object, the present invention provides a method for multi-machine cooperative dynamic task allocation of the same kind of agricultural machine, wherein the method for multi-machine cooperative dynamic task allocation of the same kind of agricultural machine is based on an improved contract network algorithm to perform dynamic task allocation, and comprises the following steps:
s100, constructing a multi-machine cooperative cost function based on the performance of the agricultural machine and the task parameters according to a multi-machine cooperative operation scene;
s200, constructing an agricultural machinery bidding cost function and a cluster cost function after bidding is completed;
s300, constructing a multi-machine collaborative dynamic task allocation system based on a remote cloud service platform and a wireless ad hoc network;
s400, when a new task needs to be distributed, the system distributes the new task by improving a contract network algorithm, and finally an optimal task distribution result is obtained.
The method for multi-machine cooperative dynamic task allocation of the same agricultural machine comprises the following steps of:
s101, defining symbols, assuming m agricultural machinery works, using a set { a }1，…，amRepresents; the number of job tasks being n, using the set { T }1，…，TnRepresents; the performance parameter of the ith agricultural machine is expressed as ai＝{vwi，di，wi，vi，tti}T(i ═ 1, 2, …, m), where vwiThe average operating speed (km/h), d of the ith agricultural machineiIndicates the working width (m), w of the ith agricultural machineiRepresents the average working capacity (m) of the ith agricultural machine2/h)，viRepresents the average running speed (km/h), t of the ith agricultural machine in the non-operation statetiThe average time (h) of each turn around in the ith agricultural machine operation is shown; the parameters for the jth task are expressed as: t isj＝{x1j，y1j，x2j，y2j，x3j，y3j，x4j，y4j，dTj，lTj，Si}T(j — 1, 2, …, n, where (x1j, y1j), (x2j, y2j), (x3j, y3j), and (x4j, y4j) respectively represent task TjCoordinates of four vertices of the plot, dTjRepresenting a task TjWidth of vertical working path, /)TjRepresenting a task TjLength of parallel working path, SjRepresenting a task TjThe area of (d);
s102, calculating the non-operation distance of each agricultural machine by adopting the following formula:
Figure BDA0002755781420000021
wherein, s (a)i，Tj) Indicating agricultural machinery aiTo its 1 st task TjDistance of (d); s (a)i，TjTk) Indicating agricultural machinery aiFrom jth task TjTo the kth task TkDistance of (d); s (a)i，Tl) Indicating agricultural machinery aiFrom the last task TlReturning to the garage; j, k, l ∈ {1, …, n };
Figure BDA0002755781420000022
Figure BDA0002755781420000031
Figure BDA0002755781420000032
s103, calculating the total time of each agricultural machine for completing tasks, wherein the total time comprises the time of the agricultural machine on the road, the time of the agricultural machine operation and the time of the agricultural machine turning around in the field;
Figure BDA0002755781420000033
wherein the content of the first and second substances,
Figure BDA0002755781420000034
kijfor the ith agricultural machine to work on the jth task land,
Figure BDA0002755781420000035
in the formula
Figure BDA0002755781420000036
The value is the smallest integer which is not less than the value in the symbol and is rounded up;
and S104, calculating the distance between tasks, taking the garage as a starting point, sequentially taking n tasks as 2 nd to n +1 th points, and establishing a shortest distance matrix D which can be driven between any two points.
The method for distributing the multi-machine cooperative dynamic tasks of the same agricultural machine comprises the following steps:
Figure BDA0002755781420000037
wherein d isijThe shortest distance which can be traveled between the i-1 st task point and the j-1 st task point is shown, (i, j ≠ j) {2, …, n +1}, i ≠ j).
In the multi-machine cooperative dynamic task allocation method for the same agricultural machinery, if the two task points are adjacent, the shortest distance which can be traveled between the two task points is considered to be 0; if the two tasks are not adjacent, the shortest distance which can be traveled between the two task points is equal to the distance on the road between the two tasks.
The method for multi-machine cooperative dynamic task allocation of the same agricultural machinery, wherein in step 102, s (a)i，Tj)＝d1，j+1，s(ai，Tl)＝d1，l+1；
The mode that the agricultural machine enters the mission plot comprises entering from the road and entering from a junction of the ground, wherein x is 0 when the agricultural machine enters the mission plot from the road, and x is 1 when the agricultural machine enters the mission plot from the junction of the ground; when the agricultural machine returns to the roadside after the task is finished, y is equal to 0, and when the agricultural machine returns to the ground connection part after the task is finished, y is equal to 1;
the agricultural machine enters from the road when entering the first task land, and the position of the ith agricultural machine after the operation of the jth task land is completed is as follows: y isij＝(kij+xij) % 2, wherein xijThe method is characterized in that the 'residue' is obtained for the mode that the ith agricultural machine enters the jth task land;
when d isj+1，k+1When not equal to 0, the ground of the tasks i and j are not connected, and the agricultural machinery a is usediDistance from task j to task k: s (a)i，TjTk)＝dj+1，k+1+yijlTj，xik0; when d isj+1，k+1When the value is equal to 0, the tasks i and j are connected, and the agricultural machinery a is in the momentiThe distance from task j to task k is:
s(ai，TjTk)＝d′j+1，k+1+|yij-1|lTj，xik＝1。
in the above method for distributing multi-machine cooperative dynamic tasks of the same agricultural machine, in step 105, the operating time of the agricultural machine with the longest operating time in multi-machine cooperation is used as the cost of multi-machine cooperation:
f＝max(ti)
the multi-machine cooperative objective function is to minimize the cost, namely:
min(f)＝min(max(ti))
wherein f represents the multi-machine cooperative cost.
The method for multi-machine cooperative dynamic task allocation of the same agricultural machine comprises the following steps of S200:
s201, constructing an agricultural machine aiFor task TjCost function of bid:
Figure BDA0002755781420000041
Figure BDA0002755781420000042
adding task T for ith agricultural machinejTotal time of the later required work; t is tmaxThe maximum working time of the whole cluster before the bidding begins;
s202, constructing the ith agricultural machine bid-winning task TjRear entire fleet cost f ═ f + Δ fi jWherein f' is the total cost of the cluster after bidding is completed; f is the multi-machine cooperation cost before bidding.
The method for multi-machine cooperative dynamic task allocation of the same agricultural machine comprises the following steps of:
s401, determining a tender taker, and selecting normal operation agricultural machinery by a platformFor the tenderer, selecting the tenderer to minimize the communication distance in the tendering process
Figure BDA0002755781420000043
Wherein (x)i，yi) The current position of the ith agricultural machine;
s402, the tenderer sets a tendering threshold value, and the tenderer is in the process of task TjBefore bidding, the minimum cost delta f for executing the task is calculatedjAs a result of the dynamic threshold value,
Figure BDA0002755781420000051
wherein
Figure BDA0002755781420000052
Performing a newly added task T for a bidderjThe cost of (d); bidder aiReceiving the bidding information and calculating the minimum cost delta f for itself to perform the taski JIf Δ fi J＜ΔfjSending bid information if Δ fi J≥ΔfjIf yes, no bidding information is sent;
s403, bidding process based on contract network algorithm with threshold value;
s404, bidding the task with the smallest area of the winning bidder;
s405, executing task exchange among agricultural machines, and setting the agricultural machine i to execute a task TjDistance cost of
Figure BDA0002755781420000053
Wherein s isi-jRemoving task T for agricultural machinery ijThe subsequent distance;
and S406, obtaining a final dynamic task allocation result.
In the above method for allocating multi-machine cooperative dynamic tasks of the same agricultural machine, the step S405 of performing task exchange between agricultural machines further includes:
s4051, calculating the maximum distance cost by the agricultural machinery i with the maximum task cost
Figure BDA0002755781420000054
And a corresponding task number j;
s4052, taking the agricultural machinery i as a tenderer to exchange and tender the task j;
s4053, using other normal agricultural machines as bidders, deleting tasks which are not executed by the bidders in sequence by the bidders in a deleting-inserting mode, and calculating the minimum cost of the bidders after replacement by using an inserting method;
s4054, if the cost after replacement is less than that before replacement, the task is used as bidding information;
s4055, the tenderer calculates the cost after adding each bidding task after deleting the task j in a 'delete-insert' mode, and takes the minimum cost fi kAnd a corresponding task k;
s4056, if fi k＜fiThen the task j, k is swapped.
The multi-machine cooperative dynamic task allocation method for the same agricultural machine is characterized in that the multi-machine cooperative dynamic task allocation system comprises the agricultural machine, a server and a client, wherein the agricultural machine is provided with a vehicle-mounted computer, a Beidou positioning module and a wireless ad hoc network module and is used for realizing self positioning and communication with other agricultural machines; the server comprises a computing module and a storage module, wherein the storage module is used for storing the plot information and the agricultural machinery information; the client is used for selecting and sending tasks to the designated operation cluster.
The invention has the technical effects that:
the invention solves the problem of how to reasonably and dynamically allocate tasks and task execution sequences under the condition that a new task is added or an agricultural machine is out of order in the operation process of a plurality of agricultural machines of the same kind in an agricultural machine cooperative society or farm.
The invention is described in detail below with reference to the drawings and specific examples, but the invention is not limited thereto.
Drawings
FIG. 1 is a flow diagram of dynamic task allocation according to an embodiment of the present invention;
FIG. 2 is a flow chart of task exchange according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail with reference to the following drawings, which are provided for illustration purposes and the like:
referring to fig. 1, fig. 1 is a flow chart of dynamic task allocation according to an embodiment of the present invention. The invention discloses a multi-machine cooperative dynamic task allocation method for the same kind of agricultural machinery, which is used for performing dynamic task allocation based on an improved contract network algorithm and comprises the following steps:
s100, constructing a multi-machine cooperative cost function based on the performance of the agricultural machine and task parameters according to a multi-machine cooperative operation scene;
s200, establishing an agricultural machinery bidding cost function and a cluster cost function after bidding is completed;
s300, constructing a multi-machine collaborative dynamic task allocation system based on a remote cloud service platform and a wireless ad hoc network; the multi-machine collaborative dynamic task allocation system can comprise an agricultural machine, a server and a client, wherein the agricultural machine can be provided with a vehicle-mounted computer, a Beidou positioning module and a wireless ad hoc network module and is used for realizing self positioning and communication with other agricultural machines; the server comprises a computing module and a storage module, wherein the storage module is used for storing the plot information and the agricultural machinery information, and the computing module is used for realizing a computing function; the client is used for selecting and issuing tasks to a designated operation cluster;
and S400, when a new task needs to be distributed, the multi-machine collaborative dynamic task distribution system distributes the new task by improving a contract network algorithm and obtains an optimal task distribution result.
Wherein, step S100 further comprises:
step S101, defining symbols, assuming m agricultural machinery works, using set { a }1，…，amRepresents; the number of job tasks being n, using the set { T }1，…，TnRepresents; the performance parameter of the ith agricultural machine is expressed as ai＝{vwi，di，wi，vi，tti}T(i ═ 1, 2, …, m), where vwiThe average operating speed (km/h), d of the ith agricultural machineiIndicates the working width (m), w of the ith agricultural machineiRepresents the average working capacity (m) of the ith agricultural machine2/h)，viRepresents the average running speed (km/h), t of the ith agricultural machine in the non-operation statetiThe average time (h) of each turn around in the ith agricultural machine operation is shown; the parameters for the jth task are expressed as: t isj＝{x1j，y1j，x2j，y2j，x3j，y3j，x4j，y4j，dTj，lTj，Si}T(j ═ 1, 2, …, n), where (x)1j，y1j)、(x2j，y2j)、(x3j，y3j) And (x)4j，y4j) Respectively represent tasks TjCoordinates of four vertices of the plot, dTjRepresenting a task TjWidth of vertical working path, /)TjRepresenting a task TjLength of parallel working path, SjRepresenting a task TjThe area of (d);
step S102, calculating the non-operation distance of each agricultural machine by adopting the following formula:
Figure BDA0002755781420000071
wherein, s (a)i，Tj) Indicating agricultural machinery aiTo its 1 st task TjDistance of (d); s (a)i，TjTk) Indicating agricultural machinery aiFrom jth task TjTo the kth task TkDistance of (d); s (a)i，Tl) Indicating agricultural machinery aiFrom the last task TlReturning to the garage; j, k, l ∈ {1, …, n };
Figure BDA0002755781420000072
Figure BDA0002755781420000073
Figure BDA0002755781420000074
step S103, calculating the total time of each agricultural machine for completing tasks, wherein the total time comprises the time of the agricultural machine on the road, the time of the agricultural machine operation and the time of the agricultural machine field turning around;
Figure BDA0002755781420000075
wherein the content of the first and second substances,
Figure BDA0002755781420000076
kijfor the ith agricultural machine to work on the jth task land,
Figure BDA0002755781420000077
in the formula
Figure BDA0002755781420000078
The value is the smallest integer which is not less than the value in the symbol and is rounded up;
and step S104, calculating the distance between tasks, taking the garage as a starting point, namely a first point, and taking n tasks as 2 nd to n +1 th points in sequence, and establishing a shortest distance matrix D which can be driven between any two points.
Wherein the shortest distance matrix D is:
Figure BDA0002755781420000081
wherein d isijThe shortest distance which can be traveled between the i-1 st task point and the j-1 st task point is shown, (i, j ≠ j) {2, …, n +1}, i ≠ j).
If the two task points are adjacent, the shortest distance which can be traveled between the two task points is considered to be 0; if the two tasks are not adjacent, the shortest distance which can be traveled between the two task points is equal to the distance on the road between the two tasks.
In step 102 of this embodiment, s (a)i，Tj)＝d1，j+1，s(ai，Tl)＝d1，l+1；
The mode that the agricultural machine enters the mission plot comprises entering from the road and entering from a junction of the ground, wherein x is 0 when the agricultural machine enters the mission plot from the road, and x is 1 when the agricultural machine enters the mission plot from the junction of the ground; when the agricultural machine returns to the roadside after the task is finished, y is equal to 0, and when the agricultural machine returns to the ground connection part after the task is finished, y is equal to 1;
the agricultural machine enters from the road when entering the first task land, and the position of the ith agricultural machine after the operation of the jth task land is completed is as follows: y isij＝(kij+xij) % 2, wherein xijThe method is characterized in that the 'residue' is obtained for the mode that the ith agricultural machine enters the jth task land;
when d isj+1，k+1When not equal to 0, the ground of the tasks i and j are not connected, and the agricultural machinery a is usediDistance from task j to task k: s (a)i，TjTk)＝dj+1，k+1+yijlTj，xik0; when d isj+1，k+1When the value is equal to 0, the tasks i and j are connected, and the agricultural machine a is connectediThe distance from task j to task k is:
s(ai，TjTk)＝d′j+1，k+1+|yij-1|lTj，xik＝1。
in step 105, constructing a multi-machine cooperative cost function at the cost of the farm machine operation time with the longest multi-machine cooperative operation time: max (t)i)。
The multi-machine cooperative objective function is to minimize the cost, namely:
min(f)＝min(max(ti))
wherein f represents the multi-machine cooperative cost.
In this embodiment, step S200 further includes:
step S201, constructing agricultural machinery aiFor task TjCost function of bid:
Figure BDA0002755781420000091
Figure BDA0002755781420000092
adding task T for ith agricultural machineryjTotal time of the later required work; t is tmaxThe maximum working time of the whole cluster before the bidding begins;
step S202, constructing the ith agricultural machinery bid-winning task TjThe rear whole cluster cost f ═ f + Δ fi jWherein f' is the total cost of the cluster after bidding is completed; f is the multi-machine cooperation cost before bidding.
Step S400 further includes:
step S401, determining a tenderer, selecting a normal operation agricultural machine as the tenderer by the platform, and selecting the tenderer to make the communication distance in the tendering process shortest
Figure BDA0002755781420000093
Wherein (x)i，yi) The current position of the ith agricultural machine;
step S402, the tenderer sets a tendering threshold value, and the tenderer is in the process of task TjBefore bidding, the minimum cost delta f for executing the task is calculatedjAs a result of the dynamic threshold value,
Figure BDA0002755781420000094
wherein
Figure BDA0002755781420000095
Performing a newly added task T for a bidderjThe cost of (d); bidder aiReceiving the bidding information and calculating the minimum cost delta f for itself to perform the taski JIf Δ fi J＜ΔfjSending bid information if Δ fi J≥ΔfjIf yes, no bidding information is sent;
step S403, bidding based on contract network algorithm with threshold value;
s404, bidding the task with the smallest area of the winning bidder;
step S405, executing task exchange among agricultural machines, and setting an agricultural machine i to execute a task TjDistance cost of
Figure BDA0002755781420000096
Wherein s isi-jRemoving task T for agricultural machinery ijThe subsequent distance;
and step S406, obtaining a final dynamic task allocation result.
Referring to fig. 2, fig. 2 is a task exchange flow chart according to an embodiment of the present invention. In this embodiment, the step S405 of performing task exchange between agricultural machines further includes:
step S4051, calculating the maximum distance cost by the agricultural machinery i with the maximum task cost
Figure BDA0002755781420000097
And a corresponding task number j;
s4052, the agricultural machinery i serves as a tenderer to exchange and tender the task j;
s4053, using other normal agricultural machines as bidders, deleting tasks which are not executed by the bidders in sequence by the bidders in a deleting-inserting mode, and calculating the minimum cost of the bidders after replacement by using an inserting method;
step S4054, if the cost after replacement is less than that before replacement, the task is used as bidding information;
step S4055, the tenderer calculates the cost after adding each bidding task after deleting task j by using a 'delete-insert' mode, and takes the minimum cost fi kAnd a corresponding task k;
step S4056, if fi k＜fiThen the task j, k is swapped.
The invention solves the problem of how to reasonably and dynamically allocate tasks and task execution sequences under the condition that a new task is added or the agricultural machinery has a fault in the operation process of a plurality of agricultural machinery of the same kind in an agricultural machinery cooperative society or a farm.
The present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof, and it should be understood that various changes and modifications can be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (10)

1. A multi-machine cooperative dynamic task allocation method for the same agricultural machine is characterized in that the dynamic task allocation method for the same agricultural machine is based on an improved contract network algorithm to perform dynamic task allocation, and comprises the following steps:
s100, constructing a multi-machine cooperative cost function based on the performance of the agricultural machine and the task parameters according to a multi-machine cooperative operation scene;
s200, constructing an agricultural machinery bidding cost function and a cluster cost function after bidding is completed;
s300, constructing a multi-machine collaborative dynamic task allocation system based on a remote cloud service platform and a wireless ad hoc network; and
and S400, when a new task needs to be distributed, the system distributes the new task by improving a contract network algorithm and obtains an optimal task distribution result.
2. The multi-machine cooperative dynamic task allocation method for the same agricultural machine as in claim 1, wherein the step S100 further comprises:
s101, defining symbols, assuming m agricultural machinery works, using a set { a }1，…，amRepresents; the number of job tasks being n, using the set { T }1，…，TnRepresents; the performance parameter of the ith agricultural machine is expressed as ai＝{vwi，di，wi，vi，tti}T(i ═ 1, 2, …, m), where vwiThe average operating speed (km/h), d of the ith agricultural machineiIndicates the working width (m), w of the ith agricultural machineiRepresents the average working capacity (m) of the ith agricultural machine2/h)，viRepresents the average running speed (km/h), t of the ith agricultural machine in the non-operation statetiThe average time (h) of each turn around in the ith agricultural machine operation is shown; the parameters for the jth task are expressed as: t isj＝{x1j，y1j，x2j，y2j，x3j，y3j，x4j，y4j，dTj，lTj，Si}T(j — 1, 2, …, n, where (x1j, y1j), (x2j, y2j), (x3j, y3j), and (x4j, y4j) respectively represent task TjCoordinates of four vertices of the plot, dTjRepresenting a task TjWidth of vertical working path, /)TjRepresenting a task TjLength of parallel working path, SjRepresenting a task TjThe area of (d);
s102, calculating the non-operation distance of each agricultural machine by adopting the following formula:
Figure FDA0002755781410000011
wherein, s (a)i，Tj) Indicating agricultural machinery aiTo its 1 st task TjDistance of (d); s (a)i，TjTk) Indicating agricultural machinery aiFrom jth task TjTo the kth task TkDistance of (d); s (a)i，Tl) Indicating agricultural machinery aiFrom the last task TlReturning to the garage; j, k, l ∈ {1, …, n };
Figure FDA0002755781410000021
Figure FDA0002755781410000022
Figure FDA0002755781410000023
s103, calculating the total time of each agricultural machine for completing tasks, wherein the total time comprises the time of the agricultural machine on the road, the time of the agricultural machine operation and the time of the agricultural machine turning around in the field;
Figure FDA0002755781410000024
wherein the content of the first and second substances,
Figure FDA0002755781410000025
kijfor the ith agricultural machine to work on the jth task land,
Figure FDA0002755781410000026
in the formula
Figure FDA0002755781410000027
The value is the smallest integer which is not less than the value in the symbol and is rounded up;
and S104, calculating the distance between tasks, taking the garage as a starting point, sequentially taking n tasks as 2 nd to n +1 th points, and establishing a shortest distance matrix D which can be driven between any two points.
3. The multi-machine cooperative dynamic task allocation method for the same agricultural machine as claimed in claim 2, wherein the shortest distance matrix D is:
Figure FDA0002755781410000028
wherein d isijThe shortest distance which can be traveled between the i-1 st task point and the j-1 st task point is shown, (i, j ≠ j) {2, …, n +1}, i ≠ j).
4. The multi-machine cooperative dynamic task allocation method of the same agricultural machine as claimed in claim 2 or 3, wherein if two tasks are adjacent in ground, the shortest distance that can be traveled between the two task points is considered to be 0; if the two tasks are not adjacent, the shortest distance which can be traveled between the two task points is equal to the distance on the road between the two tasks.
5. The method as claimed in claim 4, wherein in step 102, s (a) isi，Tj)＝d1，j+1，s(ai，Tl)＝d1，l+1；
The mode that the agricultural machine enters the mission plot comprises entering from the road and entering from a junction of the ground, wherein x is 0 when the agricultural machine enters the mission plot from the road, and x is 1 when the agricultural machine enters the mission plot from the junction of the ground; when the agricultural machine returns to the roadside after the task is finished, y is equal to 0, and when the agricultural machine returns to the ground connection part after the task is finished, y is equal to 1;
the agricultural machine enters from the road when entering the first task land, and the position of the ith agricultural machine after the operation of the jth task land is completed is as follows: y isij＝(kij+xij) % 2, wherein xijThe method is characterized in that the 'residue' is obtained for the mode that the ith agricultural machine enters the jth task land;
when d isj+1，k+1When not equal to 0, the ground of the tasks i and j are not connected, and the agricultural machinery a is usediDistance from task j to task k: s (a)i，TjTk)＝dj+1，k+1+yijlTj，xik0; when d isj+1，k+1When the value is equal to 0, the tasks i and j are connected, and the agricultural machine a is connectediThe distance from task j to task k is:
s(ai，TjTk)＝d′j+1，k+1+|yij-1|lTj，xik＝1。
6. the multi-machine cooperative dynamic task allocation method for the same agricultural machine as in claim 5, wherein in step 105, a multi-machine cooperative cost function is constructed at the cost of the agricultural machine operation time with the longest multi-machine cooperative operation time: max (t)i)。
The multi-machine cooperative objective function is to minimize the cost, namely:
min(f)＝min(max(ti))
wherein f represents the multi-machine cooperative cost.
7. The multi-machine cooperative dynamic task allocation method for the same agricultural machine as claimed in claim 6, wherein the step S200 further comprises:
s201, constructing an agricultural machine aiFor task TjCost function of bid:
Figure FDA0002755781410000031
wherein
Figure FDA0002755781410000032
Figure FDA0002755781410000033
Adding task T for ith agricultural machineryjTotal time of the later required work; t is tmaxThe maximum working time of the whole cluster before the bidding begins;
s202, constructing the ith agricultural machine bid-winning task TjThe rear whole cluster cost f ═ f + Δ fi jWherein f' is the total cost of the cluster after bidding is completed; f is the multi-machine cooperation cost before bidding.
8. The multi-machine cooperative dynamic task allocation method for the same agricultural machine as claimed in claim 7, wherein the step S400 further comprises:
s401, determining a bid inviting person, selecting a normal operation agricultural machine as the bid inviting person by the platform, and selecting the bid inviting person to ensure that the communication distance in the bid inviting process is shortest
Figure FDA0002755781410000041
Wherein (x)i，yi) The current position of the ith agricultural machine;
s402, the tenderer sets a tendering threshold value, and the tenderer is in the process of task TjBefore bidding, the minimum cost delta f for executing the task is calculatedjAs a result of the dynamic threshold value,
Figure FDA0002755781410000042
wherein
Figure FDA0002755781410000043
Performing a newly added task T for a bidderjThe cost of (d); bidder aiReceiving the bidding information and calculating the minimum cost delta f for itself to perform the taski jIf Δ fi j＜ΔfjSending bid information if Δ fi j≥ΔfjIf yes, no bidding information is sent;
s403, bidding process based on contract network algorithm with threshold value;
s404, bidding the task with the smallest area of the winning bidder;
s405, executing task exchange among agricultural machines, and setting the agricultural machine i to execute a task TjDistance cost of
Figure FDA0002755781410000044
Wherein s isi-jRemoving task T for agricultural machinery ijThe subsequent route;
and S406, obtaining a final dynamic task allocation result.
9. The method for multi-machine cooperative dynamic task allocation of the same agricultural machine as in claim 8, wherein the step S405 of performing inter-agricultural-machine task exchange further comprises:
s4051, calculating the maximum distance cost by the agricultural machinery i with the maximum task cost
Figure FDA0002755781410000045
And a corresponding task number j;
s4052, taking the agricultural machinery i as a tenderer to exchange and tender the task j;
s4053, using other agricultural machines which normally work as bidders, deleting tasks which are not executed by the bidders in sequence by using a deleting-inserting mode, and calculating the minimum cost of the bidders after replacement by using an inserting method;
s4054, if the cost after replacement is less than that before replacement, the task is used as bidding information;
s4055, the tenderer calculates the cost after adding each bidding task after deleting the task j in a 'delete-insert' mode, and takes the minimum cost fi kAnd a corresponding task k;
s4056, if fi k＜fiThen the task j, k is swapped.
10. The multi-machine cooperative dynamic task allocation method of the same agricultural machine as claimed in claim 9, wherein the multi-machine cooperative dynamic task allocation system in step S300 includes an agricultural machine, a server and a client, the agricultural machine is equipped with a vehicle-mounted computer, a beidou positioning module and a wireless ad hoc network module for realizing self-positioning and communication with other agricultural machines; the server comprises a computing module and a storage module, wherein the storage module is used for storing the land parcel information and the agricultural machinery information; the client is used for selecting and sending tasks to the designated operation cluster.
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117621091A (en) * 2024-01-26 2024-03-01 深圳威洛博机器人有限公司 Gait cooperative control method and system for robot

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117621091A (en) * 2024-01-26 2024-03-01 深圳威洛博机器人有限公司 Gait cooperative control method and system for robot
CN117621091B (en) * 2024-01-26 2024-04-09 深圳威洛博机器人有限公司 Gait cooperative control method and system for robot

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