KR100298765B1 - The optimum path determining device - Google Patents

Abstract

The present invention relates to an optimal route determining apparatus for determining an optimal route by connecting a starting point and a target point in an unmanned transportation system of a factory or the like, and has an object of simply determining an optimal route for a regular traveling route, To this end, the static graph generating unit 10 groups the nodes that can run on the basis of the distance between the nodes or the travel time of the traveling route, calculates a first cost for each mark, and when the target node is indicated, A second cost is calculated based on the direction of each node constituting each mark viewed from the target node by the unit 11, these costs are added for each mark, and the optimum path generator 9 calculates, As the optimal route from the start position to the end position of the mark.

Description

The optimum path determining device

FIG. 1 is a block diagram of an embodiment of the present invention,

FIG. 2 is a configuration diagram of the trapezoidal traveling path according to the present invention,

FIG. 3 is a schematic view of another trapezoid traveling path of the present invention,

FIG. 4 also shows the result of cost calculation in the embodiment of the present invention,

5 shows the result of the cost calculation in the embodiment of the present invention,

FIG. 6 is a diagram showing data such as coordinates of the trapezoidal traveling path according to the present invention,

FIG. 7 shows a conventional cost calculation and shortest path selection result table,

FIG. 8 is a diagram showing coordinate data of a trapezoid traveling path according to the present invention,

FIG. 9 is a block diagram of a conventional invention; FIG.

Description of the Related Art

8, 18: graph generator (adding means) 9, 19: optimum path generator (path generating means)

10: static graph generating unit (first cost generating means)

11: Angular potential calculation unit (second cost generation means)

The present invention relates to an optimum path determining apparatus for determining an optimum path by connecting a starting point and a target point in an unmanned transportation system such as a factory.

The present inventor first proposed a method using the configuration shown in FIG. 9 (Japanese Patent Application No. 3-141373) as an optimal path determination device in which the data setting is minimized in the unmanned conveyance system.

Fig. 9 shows the configuration of the unmanned conveyance vehicle. The map data memory 16 stores map data of the running route. The coordinates of the node where the unmanned return vehicle can be stopped on the running route, Is stored. In the unmanned conveying path data memory 17, data such as the speed of the unmanned conveying vehicle is stored.

Further, the graph generator 18 creates the graph Go displayed below.

Go = (N, A, Co) ----------- (1)

Here, N = {n ₁ , n ₂ , ..., n _m } is a set of nodes numbered by all nodes based on map data, and m is the number of nodes.

_{A = {a 1, a 2} , --- a n} is the two nodes n _i, n _j adjacent randomly each time, and to the end, connecting the positive node if possible travel between the two marks a node _k = {n _i , n _j } is a set of marks all numbered in order, and n is the number of marks.

Co is a set of costs calculated for each mark a _k = {n _i , n _j } based on a cost calculation index such as a distance between nodes.

The optimum path generator 19 obtains the starting node and the target node from the transfer instruction given when the transfer instruction is sent from the control station (not shown) to this unmanned conveyance vehicle. Thus, an optimal path is generated so as to minimize the integration cost based on this and the graph Go obtained in the graph generator 18, the map data, and the unmanned conveyance path data.

Here, as the index of cost calculation in each mark a _k = {n _i , n _j }, it is also possible to consider the directionality of the path (c) in addition to (a) the distance between nodes, (b)

(a), the cost B _ij of the mark from the node i to the node j can be obtained by the following equation (1).

B _ij = d _ij ------- (1)

d _ij is the straight line distance (mm) between the start point node i and the end point node j,

_{d ij = {(x j -} x i) 2 + (Y j - Y i) 2} 1/2 ----- (2)

.

Here, X _i and Y _i are the X and Y coordinates (mm) of the node i, and X _j and Y _j are the X and Y coordinates (mm) of the node j.

(b), the cost B _ij of the mark from the node i to the node j is obtained by the following equation (3).

B _ij = d _ij / v _{ij -} (3)

Since the distance d _ij is obtained in the same manner as described above and v _ij is the moving speed (m / sec) from the node i to the node j, B _ij is an amount corresponding to the moving time between nodes.

(c), the cost B _ij of the mark from the node i to the node j is obtained by the following equation (4).

B _ij = (d _ij / v _ij ) (1-p _ij ) ----- (4)

The distance d _ij and the velocity v _ij are obtained in the same manner as described above, and p _ij is a penalty coefficient indicating "good" by the directionality of the path. For example, if the direction from the node i to the node j is in the "bad" direction (reverse direction), p _ij is a negative number and the cost is raised. If p _ij is positive, It is possible to lower the cost by water. The absolute value of the coefficient p _ij is set in the range of "0 to 1" corresponding to the degree of goodness.

When an appropriate penalty coefficient is set for all the marks, only one path is obtained, in which the cost of connecting any two points (start point and target point) is minimized (hereinafter referred to as the shortest path).

However, in setting the penalty coefficient appropriately for all the marks, the influence of the penalty coefficient on the path search must be carefully considered, which is very troublesome. However, when the cost is calculated by the equation (1) or (3) without considering the penalty coefficient, the following problem arises.

Generally, as a travel route, there are most cases a case where a trapezoid shown in FIG. 2 or a square lattice shown in FIG.

The trapezoidal road of FIG. 2 is constituted by nodes of " 28 ". 6 (A) is (X, Y) coordinate data of each node.

Fig. 6 (b) shows the node number, direction, and speed data of the start point and the end point integrated for all scenes that can be moved in the trapezoid road. Here, the directionality of the path is not considered, and the direction data is all " 0 ".

In addition, since the moving speed is different in the horizontal direction and the vertical direction, the calculation is performed by Expression (3) that considers the moving speed at the cost.

Fig. 7 (a) shows the result of the calculation next to each mark. Here, the cost of the mark whose start point and end point are opposite to each other is equal, and for example, the cost of the mark with respect to the node 1,

B ₁₂ = d ₁₂ / v ₁₂ = {(4000-1000) ² + (0-0) ² } ^1/2 / (1000/1000)

Quot; 3000 " Here, the speed is subtracted to " 1000 " in order to match the unit of the expression (3). The same is true for other marks.

In order to determine the shortest path from the node 1 to the node 28 based on this data, a path for minimizing the total cost by integrating the cost for each running mark may be selected. However, as shown in Fig. 7 (b), there are eight shortest paths such as total cost.

In addition, the trapezoid running path of FIG. 3 is composed of nodes of " 100 ". FIG. 8 is (X, Y) coordinate data of each node.

Here, the moving speed between the nodes is completely the same (100 mm / sec), and scene data is omitted. Further, since the distance between adjacent nodes is all 1 m, the cost of each mark calculated by the formula (1) or (3) is all the same (1000).

Generally, the number of the shortest paths from the lower left node to the upper right node in the p trajectory,

N (p, q) = _{p + q - 2} C _{p - 1} ---- (5)

. Thus, by calculating the shortest path from the node 1 to the node 100 in the traveling path of Fig. 3,

[Equation 1]

The path of one is selected as the same condition.

As described above, according to the deadline calculation method only by the distance between the nodes constituting each mark or the shift time, the path including the original bad direction and the path frequently required for the direction change are all selected under the same condition. Therefore, it has been difficult to determine a true optimum path.

SUMMARY OF THE INVENTION The present invention has been made in consideration of the above-described circumstances, and an object thereof is to provide an optimum route determining apparatus capable of easily determining an optimum route even for a regular traveling route.

In order to solve the above problems, in the present invention, for a plurality of nodes that are dotted on a traveling route, for a set of marks that connect adjacent first movable and second movable nodes, A first cost calculation means for calculating a first cost for each mark based on a distance or a movement time, and a second cost calculation means for calculating an angle difference between a direction of the first node and a predetermined direction from the target node Second cost calculating means for calculating an angle difference between the direction of the second node and the predetermined direction and calculating a second cost for each mark based on a difference between both angular differences; For each of the marks, a cost calculation result by the cost calculation means of the cost calculation means, and an adding means for adding an optimum path from the starting node to the target node based on the adding cost calculated by the adding means And a path generation unit that selects a case where the integrated value of the addition cost of each mark is minimized.

In the above arrangement, the first cost is calculated for each mark by the first cost calculation means based on the distance between the nodes or the movement time. In addition, when the target node is indicated, the angle difference between the direction of the first node viewed from the target node and the predetermined direction by the second cost calculation means, the angle difference between the direction of the second node viewed from the target node, And the second cost is calculated for each mark based on the difference between the angular differences. Thus, these costs are added for each mark by the addition means. The path generating means selects the case where the integrated value of the add cost of each mark is minimized as the optimum path from the start node to the target node.

[Example]

Hereinafter, one embodiment of the present invention will be described with reference to the drawings.

FIG. 1 is a block diagram of an optimum path determining apparatus according to the present embodiment, and the same reference numerals are given to portions common to the ninth embodiment, and the description thereof is omitted.

In the figure, the graph generator 8 creates the graph G shown below.

G = (N, A, C) ----- (2)

Here, N = {n ₁ , n ₂ , - n _m } and A = {a ₁ , a ₂ , - a _n } are the same as the respective elements of the graph Go described above, and a description thereof will be omitted.

C is a set of costs calculated for each mark ak = {n _i , n _j } based on the index of the cost calculation with the angular potential added to the distance or movement time between the above-mentioned nodes and described below.

The static graph generation unit 10 calculates the cost B _ij of each mark by equation (1), (3), or (4) when the map data memory 16 is updated.

The angular potential calculation section 11 calculates the angular potential cost T _ij by the following equations (7) and (8) for each mark when the target node g is indicated.

T _ij (g) = (K / 2?) ?? (g, i, j) B _ij- (7)

? (G, i) |,?} - (8) ?? (g, i,

Here, K is a predetermined coefficient, and θ (g, i) is an angle obtained by measuring the direction of the node i viewed from the node g in the counterclockwise direction on the X axis, and is set to "0" when g = i. The expression (8) represents the remainder when? (G, j) -? (G, i) is divided by?.

That is, for each node i and j constituting each mark, an angle difference between the direction of the node i viewed from the target node g and the X axis direction, an angle difference between the direction of the node j seen from the target node g and the X axis direction . Therefore, the cost B _ij is multiplied by the coefficient set based on the difference between the angular differences, and a new cost T _ij (g) is calculated.

Thus, the cost C _ij (g) (= c) described below is stored in the search graph data memory 12.

C _ij (g) = B _ij + T _ij (g) - (9)

In other words, the set C _ij (g) of the cost of the mark depends on the target node in addition to the start and end nodes of each mark.

The optimum path generator 9 receives the return instruction from the control station and obtains the starting node and the target node as in the conventional case. Therefore, an optimum path is generated so as to minimize the integration cost based on the graph G, the map data, and the unmanned conveyance path data obtained in this and the graph generator 8.

The case where the target node is set to " 28 " in the trapezoid running path of Fig. 2 is considered. First, the cost B _ij (conventional cost) shown in FIG. 7 (a) is created by the static graph generating unit 10.

Next, the angular potential calculation unit 11 calculates the angular potential cost T _ij {28} shown in FIG. 4 (a). Here, the coefficient K is " 1 ".

Thus, the cost B _{ij and the} angular potential cost T _ij {28} are added to each mark _and stored in the search graph data memory 12 as the cost C _ij {28}. Fig. 4 (a) shows the calculation result of the cost _Cij {28}.

Thus, in the conventional method, the shortest path from the node 1 to the node 28 in which there are "8" branches is "1 → 15 → 16 → 17 → 18 → 19 → 20 → 21 → 22 → 23 → 24 → 25 → 26 → 27 → 28 ".

It is also assumed that the target node is set to " 100 " in the trapezoidal travel path shown in Fig. In this case also, the cost B _ij and the angular potential cost T _ij {100} are calculated in the same manner as described above, and the cost C _ij {100} in which both are added is stored in the search graph data memory 12. FIG. 5 shows the calculation result of the cost C _ij {100}.

Thus, in the conventional method, the shortest path from the node 1 to the node 100 in which there are "48620" branches is "1 → 11 → 21 → 31 → 41 → 51 → 61 → 71 → 81 → 91 → 92 → 93 → 94 → 95 → 96 → 97 → 98 → 99 → 100 ".

By the way, in the trapezoid traveling road, the unmanned return vehicle mainly moves in the horizontal direction, and the stations used for loading and unloading the work are installed in the vertical direction of the traveling road. Further, in the case where a large number of unmanned conveyance vehicles run in such a slender and long running road, the risk of interfering with each other is small.

In the case of an unmanned conveyance vehicle that travels while measuring the distance from the wall in the up and down direction by ultrasonic waves, positioning is ensured in the station as long as a long distance as possible in front of the target node is moved in the horizontal direction.

Any of the shortest paths determined in the above embodiment tends to continue in the horizontal or vertical direction marks. In addition, it is easy to select a soft path outside the traveling path. This is also the result of adding the angular potential cost, thus making it possible to determine the shortest path that more satisfies the desire for the working environment as described above.

As described above, according to the present invention, in addition to the first cost for each mark calculated based on the distance or movement time between nodes, the second cost is calculated based on the direction of each node constituting each mark viewed from the target node It is possible to easily determine the optimum route even for a regular traveling route.

Claims (1)

A cost for calculating a first cost for each mark based on a distance or a moving time between the adjacent nodes in a set of marks that are grouped by the first and second movable nodes for a plurality of nodes dotted on the traveling path, An angle difference between a direction of the first node viewed from the target node and a predetermined direction when the target node is indicated and an angle difference between the direction of the second node viewed from the target node and the predetermined direction, A second cost calculation means for calculating a second cost for each mark based on a difference between both angles of difference, an addition means for adding a cost calculation result by the first and second cost calculation means for each of the marks, And a case in which the integrated value of the addition cost of each mark is minimized as the optimum route from the starting node to the target node due to the addition cost calculated by the addition means is selected The optimum route determination apparatus comprising a path and generating means.