CN114705194A - Multi-agricultural-machinery cooperative global path conflict detection method based on topological map and time window - Google Patents
Multi-agricultural-machinery cooperative global path conflict detection method based on topological map and time window Download PDFInfo
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Abstract
The invention relates to a multi-agricultural-machine cooperative global path conflict detection method based on a topological map and a time window. Firstly, according to road information in a farmland operation environment map, calculating plane coordinates of each node and weight information of each side, and constructing a farmland operation environment topological map; secondly, carrying out global path optimization by using a Dijkstra algorithm to generate a pre-planned path set from path starting nodes to path target nodes of all tasks in a task list; then, according to the path pre-planning result, carrying out global path conflict detection based on the time windows, judging whether the time windows of all task paths have conflicts or not, and carrying out conflict classification; and finally, selecting a conflict solution strategy with the least time consumption according to the task priority and the conflict type by adopting a corresponding waiting strategy or a path change strategy, and generating a time window of each path to obtain a safe and efficient multi-agricultural-machine cooperative operation global path planning scheme.
Description
Technical Field
The invention relates to the field of artificial intelligence and the technical field of multi-machine cooperative automatic navigation, in particular to a multi-agricultural-machine cooperative global path conflict detection method based on a topological map and a time window.
Background
With the development of advanced technologies such as artificial intelligence, big data, internet of things and the like, the agricultural production mode rapidly advances from mechanization to automation and intellectualization, novel concepts such as intelligent agriculture, unmanned farms and the like appear in succession, the operation mode of cooperative navigation of a plurality of same-species or different-species agricultural machines in the field becomes the key point of agricultural machine navigation research, and the research mainly focuses on two aspects of a fleet positioning technology and a formation maintaining control technology.
The multi-machine collaborative operation path planning is one of key problems in the collaborative navigation field, and the high-efficiency, reasonable, safe and reliable path planning can improve the execution efficiency of the whole system and reduce the execution cost. Foreign and domestic scholars have achieved more achievements in the aspect of multi-machine collaborative path planning, and research methods are continuously innovated, but still have certain limitations. Most research achievements are applied to the fields of multi-unmanned aerial vehicle cooperation, multi-robot cooperation and automatic driving automobiles, the field of agricultural machinery cooperation navigation combined with an actual agricultural application scene is less in research, and few instances of unmanned operation are realized in the real sense through robot group cooperation in actual agricultural production.
In addition, in actual farmland operation, multi-machine collaborative path planning is an optimization problem under a multi-constraint condition, and besides the path cost is enabled to be as low as possible, the path safety among multiple machines is ensured to be collision-free. The current farm machine group cooperative operation and remote intelligent scheduling scheme does not consider a more complex and dynamic farm machine group working environment, and is difficult to meet the production requirement of an unmanned intelligent farm. Therefore, in order to truly realize unmanned operation, the agricultural machine group cooperative control model for the whole process of farming management and harvesting has important theoretical significance and good application prospect by theoretically researching the multi-agricultural machine group operation path planning technology, the response mechanism facing sudden situations in the multi-agricultural machine group operation process and the like.
Disclosure of Invention
Aiming at the technical problems, the invention aims to provide a multi-agricultural-machine collaborative global path conflict detection method based on a topological map and a time window, which obtains a safe, efficient and conflict-free multi-agricultural-machine collaborative global operation path by analyzing the multi-machine collaborative operation constraint problem in a farmland operation environment and taking the minimized path cost and the minimized operation time as optimization targets, so that agricultural machines can orderly serve farmland operation plots, a scheduling model with short path, high efficiency, safety and reliability is established, support is provided for further solving multi-machine collaborative operation path planning in a regional farmland complex operation environment, and a technical scheme is provided for promoting unmanned farm construction.
When a plurality of agricultural machines operate in the same farmland area, a plurality of optimal paths need to be planned, but in the specific operation process, because the farmland operation environment has more obstacles and the agricultural machines can influence each other to become the obstacles of each other, the paths may conflict with each other, and therefore, the problem of global path conflict of multi-agricultural machine cooperative operation needs to be solved in the actual operation.
The essence of the multi-agricultural-machine cooperative path conflict is that a plurality of agricultural machines occupy the same path point at the same time point, so that planning needs to be carried out in combination with a time window in actual operation, and a multi-agricultural-machine cooperative global operation path planning model based on time window conflict detection is constructed aiming at an actual farmland operation scene, thereby solving the problem of multi-agricultural-machine cooperative global operation path conflict.
The essence of the multi-machine cooperative global operation path conflict is that a plurality of agricultural machines occupy the same path point at the same time point, and the time window records the time and the place of the operation agricultural machine in detail, so as to provide a precondition for judging and solving the path conflict problem, therefore, the planning needs to be carried out by combining the time window, and a multi-agricultural machine cooperative global path planning model based on time window conflict detection is constructed aiming at the actual farmland operation scene by taking the minimized path cost and the operation time as optimization targets.
In order to achieve the purpose, the invention provides the following technical scheme:
a multi-agricultural-machinery cooperation global path conflict detection method based on a topological map and a time window comprises the steps of firstly, calculating plane coordinates of each node and weight information of each side according to road information in a farmland operation environment map, and constructing the farmland operation environment topological map; secondly, carrying out global path optimization by using a Dijkstra algorithm to generate a pre-planned path set from path starting nodes to path target nodes of all tasks in a task list; then, according to the path pre-planning result, carrying out global path conflict detection based on the time windows, judging whether the time windows of all task paths have conflicts or not, and carrying out conflict classification; and finally, selecting a conflict solution strategy with the least time consumption according to the task priority and the conflict type by adopting a corresponding waiting strategy or a path change strategy, and generating a time window of each path to obtain a safe and efficient multi-agricultural-machine cooperative operation global path planning scheme.
A multi-agricultural-machinery cooperative global path conflict detection method based on a topological map and a time window comprises the following steps:
s1, establishing an environment map;
calculating plane coordinates of each node and weight information of each edge according to road information in a farmland operation environment map, and constructing a farmland operation environment topological map, wherein the nodes represent road intersection points, current coordinate positions of agricultural machines or position coordinates of tasks, the edges represent roads on which the agricultural machines run, and the weight information is the distance between two nodes forming the edges;
s2, path pre-planning;
setting a path starting node, a path target node and task priorities according to the plane coordinates of each node and the weight information of each edge in the farmland operation environment topological map obtained in the step S1, wherein the path starting node is the current coordinate position of the agricultural machine, the path target node is the position coordinates of the tasks, and each task is executed by one agricultural machine; according to a path cost minimization principle, carrying out global path optimization by using a Dijkstra algorithm to generate a pre-planned path set from path starting nodes to path target nodes of all tasks in a task list;
s3, path conflict detection;
judging whether the same nodes and node intervals exist among all task paths in the pre-planned path set or not according to the pre-planned path set of all tasks obtained in the step S2; if the same node and node interval do not exist, obtaining an optimal path set and finishing path planning; if the same node and the same node interval exist, time windows of all task paths are generated according to agricultural machinery information and task priorities, global path conflict detection is carried out on the basis of the time windows, and whether conflicts exist in the time windows of all task paths is judged; the agricultural machinery information comprises acceleration time, uniform speed time, braking time, turning time and operation time of the agricultural machinery; the task priority is the time sequence for generating the tasks;
if no time window conflict exists, obtaining an optimal path set and finishing path planning;
if the time window conflict exists, after the conflict classification is carried out, executing step S4 to re-plan the path;
the multi-machine cooperative operation global path conflict type is divided into interval type conflict and node type conflict;
the interval type conflict comprises a same-direction conflict and a opposite-direction conflict; the same-direction conflict means that when two agricultural machines drive in the same direction on the same road section, the rear vehicle speed is higher than that of the front vehicle, so that the rear-end collision of the agricultural machines can be caused; the opposite conflict refers to the condition that when two agricultural machines run in opposite directions on the same road section, the agricultural machines collide at a certain moment;
the node type conflict refers to the situation that two agricultural machines in different driving directions reach the intersection point of the same road at the same time, so that the agricultural machines collide with each other, and the situation comprises the situation that the two agricultural machines simultaneously go straight, the two agricultural machines simultaneously turn, or one agricultural machine goes straight and the other agricultural machine turns;
s4, path re-planning;
according to the task priority and the conflict type obtained in the step S3, adopting a corresponding waiting strategy or a path changing strategy to obtain a re-planned path set, and generating a time window of each path to obtain a safe, efficient and conflict-free multi-agricultural-machine cooperative global operation path;
when a path change strategy is adopted, setting the conflict nodes as temporary barrier points, and re-planning a path; in the interval conflict type, if the path of the task 1 contains the starting point of the path of the task 2, the interval conflict is contained, and a waiting strategy cannot be adopted; if the temporary barrier point is set and a path is not planned, adopting a waiting strategy; if both conflict resolution strategies can be adopted, the conflict resolution strategy with the least time consumption is selected.
In step S3, the assumed conditions for detecting a path collision using a time window are as follows:
(1) considering the agricultural machinery as mass points in the operation process, and neglecting the shape and size of the mass points;
(2) each edge in the topological map is a one-way road but can pass in two directions, and the length of each edge is ignored when the node is used as a path point;
(3) the weight information of the edges in the topological map represents the distance between nodes, and each edge only allows one agricultural machine to occupy in the same time interval;
(4) considering the acceleration and deceleration problem in the running process of the agricultural machine and the time consumed by turning;
(5) and setting task priority, wherein the default priority is the time sequence for generating the tasks.
In step S3, when calculating the time window, the agricultural machinery is at different node positions, and different time parameters are considered:
if the node is a path starting node, calculating a time window according to a formula 1;
tw (j) acquisition _ time formula 1
Wherein TW (j) represents the time window of node j in seconds; the acceleration _ time represents the acceleration time in seconds;
if the node is a constant-speed driving point, calculating a time window according to a formula 2;
TW (j) ═ TW (j-1) + uniform _ time equation 2
Wherein TW (j) represents the time window of node j in seconds; TW (j-1) represents the time window of node j-1 in seconds; the uniform time represents the uniform speed, and the unit is second;
if the node is a turning point, calculating a time window according to a formula 3;
TW (j) — TW (j-1) + uniform _ time + stop _ time + turn _ time + acquisition _ time formula 3
Wherein TW (j) represents the time window of node j in seconds; TW (j-1) represents the time window of node j-1 in seconds; the uniform time represents the uniform speed, and the unit is second; stop _ time represents braking time in seconds; turn _ time represents turning time in seconds, and accelerationtime represents acceleration time in seconds;
if the node is a path target node, calculating a time window according to a formula 4;
TW(j)＝TW(j-1)+uniformtime+stoptime+ word _ time equation 4
Wherein TW (j) represents the time window of node j in seconds; TW (j-1) represents the time window of node j-1 in seconds; uniform _ time represents constant speed time in seconds; stop _ time represents braking time in seconds; work _ time represents the working time in seconds;
wherein, the constant speed time is obtained by calculation according to the weight of the side and the speed during constant speed driving by a formula 5;
unifoFm _ time W (j-1, j)/uniform _ speed formula 5
In the formula, uniform _ time represents constant speed time, and the unit is second; w (j-1, j) represents a node, and the weight of the edge between the node j-1 and the node j is in meters; uniform _ speed represents the speed at constant speed in meters per second.
Compared with the prior art, the invention has the beneficial effects that:
the multi-agricultural-machine cooperative global path conflict detection method based on the topological map and the time window provides a scientific and reasonable scheduling management scheme for agricultural-machine management departments, can reduce scheduling cost, improve working efficiency, guide agricultural machines to perform safe and efficient scheduling, provides support for further solving multi-agricultural-machine cooperative path planning in a complex operation environment of a regional farmland, and provides a technical scheme for promoting unmanned farm construction and realizing unmanned production operation.
Drawings
FIG. 1 is a block diagram of the overall detection method for conflict of multi-farm-machinery cooperative global path based on a topological map and a time window;
FIG. 2 is a schematic diagram of interval type conflicts in accordance with the present invention;
FIG. 3 is a schematic diagram of node type conflicts in accordance with the present invention;
FIG. 4 is a 28095State trial farm topology map of the present invention;
FIG. 5 is a multi-farm-machinery collaborative pre-planning global path diagram based on a topological map and Dijkstra algorithm according to the present invention;
FIG. 6 is a diagram of a multi-farm-machinery collaborative pre-planning time window based on a topological map and Dijkstra algorithm according to the present invention;
FIG. 7 is a time window conflict detection-based multi-farm-machinery collaborative re-planning global path diagram of the present invention;
FIG. 8 is a diagram of a multi-farm machine coordinated re-planning time window based on time window conflict detection according to the present invention.
Detailed Description
The invention is further illustrated with reference to the following figures and examples.
As shown in fig. 1, a multi-farm-machinery cooperative global path conflict detection method based on a topological map and a time window includes the following steps:
s1, establishing an environment map;
calculating plane coordinates of each node and weight information of each edge according to road information in a farmland operation environment map, and constructing a farmland operation environment topological map, wherein the nodes represent road intersection points, current coordinate positions of agricultural machines or position coordinates of tasks, the edges represent roads on which the agricultural machines run, and the weight information is the distance between two nodes forming the edges;
s2, path pre-planning;
setting a path starting node, a path target node and task priorities according to the plane coordinates of each node and the weight information of each edge in the farmland operation environment topological map obtained in the step S1, wherein the path starting node is the current coordinate position of the agricultural machine, the path target node is the position coordinate of the task, and each task is executed by one agricultural machine; according to a path cost minimization principle, carrying out global path optimization by using a Dijkstra algorithm to generate a pre-planned path set from path starting nodes to path target nodes of all tasks in a task list;
when path optimization is performed on multiple tasks by using the Dijkstra algorithm, only the shortest path of each task can be planned, and no conflict between paths can be guaranteed, so that path conflict detection is required.
S3, path conflict detection;
judging whether the same nodes and node intervals exist among all task paths in the pre-planned path set or not according to the pre-planned path set of all tasks obtained in the step S2; if the same node and node interval do not exist, obtaining an optimal path set and finishing path planning; if the same node and the same node interval exist, time windows of all task paths are generated according to agricultural machinery information and task priorities, global path conflict detection is carried out on the basis of the time windows, and whether conflicts exist in the time windows of all task paths or not is judged; the agricultural machinery information comprises acceleration time, uniform speed time, braking time, turning time and operation time of the agricultural machinery; the task priority is the time sequence for generating the tasks;
if no time window conflict exists, obtaining an optimal path set and finishing path planning;
if the time window conflict exists, after the conflict classification is carried out, executing step S4 to re-plan the path;
the assumption for path collision detection using time windows is as follows:
(1) the agricultural machinery is regarded as mass points in the operation process, and the shape and the size of the mass points are ignored.
(2) Each edge in the topological map is a one-way channel but can pass in two ways, and the length of each node is ignored when the node is used as a path point.
(3) The weight information of the edges in the topological map represents the distance between the nodes, and each edge only allows one agricultural machine to occupy in the same time interval.
(4) The acceleration and deceleration problem in the running process of the agricultural machine and the time consumed by turning are considered.
(5) And setting task priority, wherein the default priority is the time sequence for generating the tasks.
When calculating the time window, the agricultural machinery is at different node positions, and different time parameters need to be considered:
if the node is a path starting node, calculating a time window according to a formula 1;
tw (j) acquisition _ time formula 1
Where TW (j) represents the time window for node j in seconds; the acceleration _ time represents the acceleration time in seconds;
if the node is a constant-speed driving point, calculating a time window according to a formula 2;
TW (j) ═ TW (j-1) + uniform _ time equation 2
Wherein TW (j) represents the time window of node j in seconds; TW (j-1) represents the time window of node j-1 in seconds; uniform _ time represents constant speed time in seconds;
if the node is a turning point, calculating a time window according to a formula 3;
TW (j-1) + uniform _ time + stop _ time + turn _ time + acquisition _ time formula 3
Wherein TW (j) represents the time window of node j in seconds; TW (j-1) represents a time window of the node j-1, and the unit of second uniform _ time represents constant speed time and the unit of second; stop _ imme represents braking time in seconds; turn _ time represents turning time in seconds, and accelerationtime represents acceleration time in seconds;
if the node is a path target node, calculating a time window according to a formula 4;
TW(j)＝TW(j-1)+uniTormtime+stoptime+ word _ time equation 4
Wherein TW (j) represents the time window of node j in seconds; TW (j-1) represents a time window of the node j-1, and the unit of second uniform _ time represents constant speed time and the unit of second; stop _ time represents braking time in seconds; work _ time represents the working time in seconds;
wherein, the constant speed time is obtained by calculating according to the weight of the edge and the speed during constant speed driving, as shown in formula 5;
equation 5 where uniform _ time is W (j-1, j)/uniform _ speed
In the formula, uniform _ time represents constant speed time, and the unit is second; w (j-1, j) represents the weight of the edge between the node j-1 and the node j, and the unit is meter; uniform _ speed represents the speed at constant speed in meters per second.
The multi-machine cooperative operation global path conflict types are divided into interval type conflicts and node type conflicts.
As shown in fig. 2, the interval type conflict includes a same-direction conflict and a same-direction conflict; the same-direction conflict means that when two agricultural machines drive in the same direction on the same road section, the rear vehicle speed is higher than that of the front vehicle, so that the rear-end collision of the agricultural machines can be caused; the opposite conflict refers to the situation that when two agricultural machines run in opposite directions on the same road section, the agricultural machines collide at a certain moment.
As shown in fig. 3, the node type conflict refers to a situation that two agricultural machines in different driving directions reach the intersection point of the same road at the same time, which may cause the agricultural machines to collide, including situations that the two agricultural machines go straight at the same time, the two agricultural machines turn at the same time, or one agricultural machine goes straight, and the other agricultural machine turns.
S4, path re-planning;
and according to the task priority and the conflict type obtained in the step S3, obtaining a re-planned path set by adopting a corresponding waiting strategy or a path changing strategy, and generating a time window of each path to obtain a safe, efficient and conflict-free multi-agricultural-machine cooperative global operation path.
When a path change strategy is adopted, setting the conflict nodes as temporary barrier points, and re-planning a path; in the interval conflict type, if the path of the task 1 contains the starting point of the path of the task 2, the interval conflict is contained, and a waiting strategy cannot be adopted; if the temporary barrier point is set and no path is planned, adopting a waiting strategy; if both conflict resolution strategies can be adopted, the conflict resolution strategy with the least time consumption is selected.
Examples
S1, constructing a topological map based on road network information of China agriculture university (28095), wherein as shown in FIG. 4, circles represent nodes, namely road junctions, current coordinate positions of agricultural machines or position coordinates of tasks, solid lines with arrows represent edges, namely roads on which the agricultural machines can run, and plane coordinates of each node and weight information of each edge in the topological map are respectively shown in tables 1 and 2.
TABLE 1\28095Jizhoutest farm topology map node XY plane coordinate
TABLE 2 28095The weights of the edges of the State trial farm topology graph (part)
S2, setting path starting nodes and target nodes (namely current coordinate positions of agricultural machinery and position coordinates of tasks) of 4 groups of tasks according to plane coordinates and weight information of each edge of each node in the State experiment farm topology map, sequencing task priorities from high to low into a pre-planned path 1, a pre-planned path 2, a pre-planned path 3 and a pre-planned path 4, and generating a pre-planned shortest path by utilizing a Dijkstra algorithm, wherein the pre-planned result is shown in a table 3 and a figure 5.
Table 3 multi-farm-machine cooperative global path preplanning result based on topological graph and Dijkstra algorithm
The starting point of the preplanned path 1 is node 1, the target point is node 36, the shortest path is [1-2-7-11-15-20-27-32-36], and the corresponding shortest distance is 531.6395 m; the starting point of the preplanned path 2 is node 12, the target point is node 27, the shortest path is [12-8-3-6-2-7-11-15-20-27], and the corresponding shortest distance is 860.3694 m; the starting point of the preplanned path 3 is a node 15, the target point is a node 31, the shortest path is [15-11-7-2-1-5-10-14-18-31], and the corresponding shortest distance is 633.0328 m; the starting point of the preplanned path 4 is node 21, the target point is node 30, the shortest path is [21-15-19-25-29-22-30], and the corresponding shortest distance is 826.1224 m.
As can be seen from the global path preplanning result in fig. 5, the positions of nodes 1, 2, 7, 11, 15, 20, and 27 of the 4 paths respectively have different path overlaps, so that it is necessary to use a time window to determine whether there is a conflict in the time of the path overlapping portion.
S3, setting relevant parameters calculated by a time window, setting the time required for acceleration, the time required for braking, the time required for turning, the time required for operation and the vehicle speed during constant speed driving to be 3S, 6S, 30S and 5m/S respectively, and setting the pre-planning time window as shown in the table 4 and the figure 6.
Table 4 multi-agricultural-machine collaborative time window preplanning result based on topological graph and Dijkstra algorithm
As can be seen from the pre-planned time windows in fig. 6, there is no time conflict between the pre-planned path 2 and other paths, while there is a time conflict between the pre-planned path 3 and the pre-planned path 1 at the node 7, and there is a time conflict between the pre-planned path 4 and the pre-planned path 1 at the node 15. According to the conflict classification result, the fact that the preplanned path 3 and the preplanned path 1 contain class interval type conflicts can be known; the pre-planned path 4 and the pre-planned path 1 are node type conflicts, and therefore, the conflict path needs to be re-planned.
S4, the path re-planning result is shown in table 5 and fig. 7.
TABLE 5 Multi-machine cooperative Global Path Replanning result based on time window Conflict detection
The starting point of the re-planned path 1 is node 1, the target point is node 36, the shortest path is [1-2-7-11-15-20-27-32-36], and the corresponding shortest distance is 531.6395 m; the starting point of the re-planned path 2 is a node 12, the target point is a node 27, the shortest path is [12-8-3-6-2-7-11-15-20-27], and the corresponding shortest distance is 860.3694 m; the starting point of the re-planned path 3 is a node 15, the target point is a node 31, the shortest path is [15-21-24-18-31], and the corresponding shortest distance is 779.6162 m; the starting point of the replanned path 4 is node 21, the target point is node 30, the shortest path is [21-15-19-25-29-22-30], and the corresponding shortest distance is 826.1224 m.
According to the global path replanning result in fig. 7, as the replanning path 3 is a path including a type conflict of class intervals, and a waiting strategy cannot be adopted, a path changing strategy is adopted, and the path is changed from [15-11-7-2-1-5-10-14-18-31] to [15-21-24-18-31 ]; the re-planning path 4 is a node type conflict, a waiting strategy is adopted, and the path is not changed.
The time window after the replanning is shown in table 6 and fig. 8.
TABLE 6 Multi-machine collaborative time window rescheduling result based on time window conflict detection
According to the path re-planning time window, although the paths of the 4 paths still overlap to different degrees, the overlapping parts of the paths after re-planning do not conflict in time. The result shows that multi-machine cooperative global path optimization and path conflict detection can be realized based on the topological map and the time window, and a conflict resolution strategy with the least time consumption is obtained, so that the safe conflict-free multi-agricultural-machine cooperative operation global shortest path is generated.
Claims (3)
1. A multi-agricultural-machinery cooperative global path conflict detection method based on a topological map and a time window is characterized by comprising the following steps:
s1, establishing an environment map;
calculating plane coordinates of each node and weight information of each edge according to road information in a farmland operation environment map, and constructing a farmland operation environment topological map, wherein the nodes represent road intersection points, current coordinate positions of agricultural machines or position coordinates of tasks, the edges represent roads on which the agricultural machines run, and the weight information is the distance between two nodes forming the edges;
s2, path pre-planning;
setting a path starting node, a path target node and task priorities according to the plane coordinates of each node and the weight information of each edge in the farmland operation environment topological map obtained in the step S1, wherein the path starting node is the current coordinate position of the agricultural machine, the path target node is the position coordinate of the task, and each task is executed by one agricultural machine; according to a path cost minimization principle, carrying out global path optimization by using a Dijkstra algorithm to generate a pre-planned path set from path starting nodes to path target nodes of all tasks in a task list;
s3, path conflict detection;
judging whether the same nodes and node intervals exist among all task paths in the pre-planned path set or not according to the pre-planned path set of all tasks obtained in the step S2; if the same node and node interval do not exist, obtaining an optimal path set and finishing path planning; if the same node and the same node interval exist, time windows of all task paths are generated according to agricultural machinery information and task priorities, global path conflict detection is carried out on the basis of the time windows, and whether conflicts exist in the time windows of all task paths is judged; the agricultural machinery information comprises acceleration time, uniform speed time, braking time, turning time and operation time of the agricultural machinery; the task priority is the time sequence for generating the tasks;
if no time window conflict exists, obtaining an optimal path set and finishing path planning;
if there is a time window conflict, after performing conflict classification, executing step S4 to re-plan the path;
the multi-machine cooperative operation global path conflict type is divided into interval type conflict and node type conflict;
the interval type conflict comprises a same-direction conflict and a opposite-direction conflict; the same-direction conflict means that when two agricultural machines drive in the same direction on the same road section, the rear vehicle speed is higher than that of the front vehicle, so that the rear-end collision of the agricultural machines can be caused; the opposite conflict refers to the condition that when two agricultural machines run in opposite directions on the same road section, the agricultural machines collide at a certain moment;
the node type conflict refers to the situation that two agricultural machines in different driving directions reach the same road intersection point at the same time, so that the agricultural machines collide with each other, and the situation comprises the situations that the two agricultural machines simultaneously go straight, the two agricultural machines simultaneously turn, or one agricultural machine goes straight, and the other agricultural machine turns;
s4, path re-planning;
according to the task priority and the conflict type obtained in the step S3, adopting a corresponding waiting strategy or a path changing strategy to obtain a re-planned path set, and generating a time window of each path to obtain a safe, efficient and conflict-free multi-agricultural-machine cooperative global operation path;
when a path change strategy is adopted, setting the conflict nodes as temporary barrier points, and re-planning a path; in the interval conflict type, if the path of the task 1 contains the starting point of the path of the task 2, the interval conflict is contained, and a waiting strategy cannot be adopted; if the temporary barrier point is set and a path is not planned, adopting a waiting strategy; if both conflict resolution strategies can be adopted, the conflict resolution strategy with the least time consumption is selected.
2. The multi-agricultural-machinery cooperative global path conflict detection method based on the topological map and the time window according to claim 1, wherein in step S3, the assumed conditions for performing the path conflict detection by using the time window are as follows:
(1) regarding agricultural machinery as mass points in the operation process, and neglecting the shape and size of the mass points;
(2) each edge in the topological map is a one-way road but can pass in two directions, and the length of each edge is ignored when the node is used as a path point;
(3) the weight information of the edges in the topological map represents the distance between nodes, and each edge only allows one agricultural machine to occupy in the same time interval;
(4) considering the acceleration and deceleration problem in the running process of the agricultural machine and the time consumed by turning;
(5) and setting task priority, wherein the default priority is the time sequence for generating the tasks.
3. The method for detecting conflict of multi-agricultural-machinery cooperative global path based on topological map and time window according to claim 1, wherein in step S3, when calculating the time window, the agricultural machinery is at different node positions, considering different time parameters:
if the node is a path starting node, calculating a time window according to a formula 1;
tw (j) acquisition _ time formula 1
Where TW (j) represents the time window for node j in seconds; the acceleration _ time represents the acceleration time in seconds;
if the node is a constant-speed driving point, calculating a time window according to a formula 2;
TW (j) ═ TW (j-1) + uniform _ time equation 2
Where TW (j) represents the time window for node j in seconds; TW (j-1) represents the time window of node j-1 in seconds; the uniform time represents the uniform speed, and the unit is second;
if the node is a turning point, calculating a time window according to a formula 3;
TW (j) — TW (j-1) + uniform _ time + stop _ time + turn _ time + acquisition _ time formula 3
Wherein TW (j) represents the time window of node j in seconds; TW (j-1) represents a time window of the node j-1, and the unit of second uniform _ time represents constant speed time and the unit of second; stop _ time represents braking time in seconds; turn _ time represents turning time in seconds, and accelerationtime represents acceleration time in seconds;
if the node is a path target node, calculating a time window according to a formula 4;
TW(j)＝TW(j-1)+uniformtime+stoptime+ word _ time equation 4
Wherein TW (j) represents the time window of node j in seconds; TW (j-1) represents the time window of node j-1 in seconds; uniform _ time represents constant speed time in seconds; stop _ time represents braking time in seconds; work _ time represents the working time in seconds;
wherein, the constant speed time is obtained by calculation according to the weight of the side and the speed during constant speed driving by a formula 5;
equation 5 where uniform _ time is W (j-1, j)/uniform _ speed
In the formula, uniform _ time represents constant speed time, and the unit is second; w (j-1, j) represents the weight of the edge between the node j-1 and the node j, and the unit is meter; uniform _ speed represents the speed at constant speed in meters per second.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115220461A (en) * | 2022-09-21 | 2022-10-21 | 睿羿科技(山东)有限公司 | Robot single system and multi-robot interaction and cooperation method in indoor complex environment |
| CN115392800A (en) * | 2022-10-28 | 2022-11-25 | 吉林省惠胜开网络科技有限公司 | Modern agricultural machinery automatic operation allocation method based on big data |
| CN116501041A (en) * | 2023-04-10 | 2023-07-28 | 安徽机电职业技术学院 | Global planning method and system for multi-robot cooperation path |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115220461A (en) * | 2022-09-21 | 2022-10-21 | 睿羿科技(山东)有限公司 | Robot single system and multi-robot interaction and cooperation method in indoor complex environment |
| CN115220461B (en) * | 2022-09-21 | 2023-02-17 | 睿羿科技(山东)有限公司 | Robot single system and multi-robot interaction cooperation method in indoor complex environment |
| CN115392800A (en) * | 2022-10-28 | 2022-11-25 | 吉林省惠胜开网络科技有限公司 | Modern agricultural machinery automatic operation allocation method based on big data |
| CN116501041A (en) * | 2023-04-10 | 2023-07-28 | 安徽机电职业技术学院 | Global planning method and system for multi-robot cooperation path |
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