CN107808059A - A kind of landform paths planning method based on directed networkses - Google Patents
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Abstract
The present invention discloses a kind of landform paths planning method based on directed networkses, and step is：(1) data prepare, and DEM regular grid data are scanned；(2) the directed networkses structure that the unit adjacent modes (3) of directed networkses structure are primary is selected；(4) beta pruning handles to obtain effective directed networkses；(5) path planning, beginning and end is given, route searching is carried out to the directed networkses using Dijsktra algorithms, finally gives the landform path of a global optimum.Present invention is fully applicable to the optimum path planning application in the terrain analysis field of extensive mass data, it is possible to increase the efficiency of path planning and global optimum.
Description
Technical field
The invention belongs to digital Terrain Analysis technology, and in particular to a kind of landform path planning side based on directed networkses
Method.
Background technology
Path planning problem be always Geographical Information Sciences, computer science, operational research, one of traffic and transport field grind
Study carefully focus.Many practical problems can be abstracted as network path planning problem, it be studied with main practical value.
Some shortest route-planning algorithms can preferably realizing route planning problem, but shortest path first is applied into complex network
During problem solving, such as network flow optimization, resource allocation, there are still computational efficiency it is low the shortcomings that.
Landform path planning refers to the minimal path that a given beginning and end is found on dimensional topography, extensive use
In traffic route planning, robot path selection etc. field.The common algorithm of landform path planning has genetic algorithm, simulation to move back
Change algorithm, ant group algorithm, A* algorithms etc..These algorithms have respective advantage and disadvantage, are adapted to different application environments.However,
It is a complicated optimal models Solve problems that path specification is carried out in three-dimensional large-scale complex landform, and the above method is all present
Convergence rate is slow, be easy to be absorbed in local optimum and can not rapid solving the problems such as.
DEM (Digital Elevation Model) model is a kind of field model, including regular grid (Regular
Square Grid, abbreviation RSG) and model and triangular irregular net (Triangulated Irregular Network, referred to as
TIN) model.Because visualization analysis and its application are all based on DEM and analyzed, these applications are taken visual feature into account and established
Various Optimized models.And path optimization model on DEM is established either in terms of modeling, or in terms of model solution all
It is more complicated, and can not be effectively improved towards the solving speed using algorithm of magnanimity dem data, even if using parallel meter
Calculation technology, but data involved in these applications have dependency characteristic, and the effect calculated can not be improved by parallelization means
Rate.
On the one hand, DEM models reflection be landform altitude field model, and in the landform that is beyond expression between grid points can
Up to relation, it is necessary to be parsed by application.Algorithm based on neighborhood search can not obtain global optimum, when in face of mass data
Usually cause data explosion problem during with complex environment information, cause algorithm almost to be stagnated.If the field that dem data is represented
Model conversion carries out path planning, so as to for using based on figure on this basis into a kind of two-dimentional directed networkses based on graph theory
Path search algorithm bring great convenience, and for terrain analysis with application establish new theoretical foundation and instrument.The opposing party
Face, with the appearance of various novel sensors and e measurement technology, dem data increases in series, so as to cause under stand-alone environment
It is a very difficult thing that large-scale data are carried out with processing.Therefore, the data based on directed networkses can use simultaneously
Row computing technique improves the efficiency of data processing.
On the digital terrain surface represented based on gridded DEM data, each grid unit can be regarded as a node,
Relation (such as distance, depth displacement etc.) between grid unit can be described as the side with weights, so as to by regular grid list
The DEM regions with 2.5 dimensions of member composition are abstracted as the virtual directed networkses with 2 dimensional plane features.Different rules
Grid unit has 4 grid unit patterns and 8 grid unit patterns substantially adjacent to pattern.Different adjacent modes are selected to depend on asking
Precision and the solution efficiency requirement of topic, and data volume and computation complexity constraint.It is based on directed networkses and on the basis of, adopt
A shortest path is quickly cooked up with existing shortest path first.
Have some prior arts for merging DEM with landform path planning at present, such as《A kind of rule-based grid
The path planning new method and flow of dem data》Belong to the DEM terrain datas based on 2.5 dimensions Deng, most of these methods and carry out
The heuritic approach of route searching is, it is necessary to which successive ignition computing, computationally intensive, and can only obtain suboptimum under time constraint condition
Solution or locally optimal solution.
The content of the invention
Goal of the invention：It is an object of the invention to solve the deficiencies in the prior art, there is provided one kind is based on direct net
The Optimization Modeling problem of landform path planning is divided into two steps to complete by the landform paths planning method of network, the present invention, first
By the data conversion of the field model of digital elevation model into the directed networkses in figure, followed by the shortest path based on directed networkses
Optimization Modeling and model rapid solving, can simplify the complexity of modeling and the efficiency of model solution.
Technical scheme：A kind of landform paths planning method based on directed networkses of the present invention, comprises the following steps：
Step 1, dem data initializes：DEM grid altitude datas are scanned according to required precision, analysed whether
Empty data on some grid units be present, if in the presence of execution interpolation calculation obtains the altitude data of the unit；
Step 2, neighbouring computation schema is selected：According to route searching required precision, the grid list of selection structure directed networkses
The neighbouring computation schema of member, this includes 4 grid unit adjacent modes (precision is low) adjacent to computation schema type and 8 grid units are neighbouring
Pattern (precision is high)；
Step 3, the weights of the arc that summit is connected in directed networkses are calculated：According to the adjacent modes of selection, calculate oriented
The weights of connection arc in network between every opposite vertexes, and then obtain the directed networkses of primary；
Step 4, directed networkses are cut：According to the constraint requirements of landform route, delete respective vertices in directed networkses and
Connection arc between summit；Final directed networkses are can obtain by beta pruning processing；
Step 5, optimum path planning：The directed networkses obtained based on step 4, path is carried out using Dijsktra algorithms and searched
Rope, starting point and terminal according to path obtain global optimum's traffic path.
In said process, the DEM terrain datas of 2.5 dimensions are first changed into the directed networkses of graph model, then can be easily
Using the classical efficient global path planning algorithm such as such as Dijkstra, Bellman-ford, realize based on directed networkses
Optimum path planning, improve the efficiency of path planning.
Further, the method for weight computing is in the step 3：
When computation schema is based on 4 grid unit adjacent modes, grid unit is regarded as along 4 directions of reference axis and connected
Connect, it is assumed that grid unit ViAnd VjHeight value be respectively EiAnd Ej, along a length of a of X-axis between grid, along a length of b of Y-axis, then direct net
The weight computing formula on the side of network is as follows：
Here, ViAnd VjIt is the grid unit point in landform, EiAnd EjV is corresponded to respectivelyiAnd VjHeight value, and a and b
It is the length of side of rectangle grid unit respectively.If grid is square, if length of side a=b=d, then formula (1) is changed into：
If being normalized, formula (2) is changed into：
When computation schema is based on 8 grid unit pattern, grid unit is regarded as in addition to 4 directions along reference axis also
4 directions connection diagonally, it is assumed that grid unit ViAnd VjHeight value be respectively EiAnd Ej, along a length of a of X-axis between grid,
Along a length of b of Y-axis, then the weights on the side of figure network are：
If square grid, i.e. a=b=d, then formula (4) is changed into：
It is normalized, then formula (5) is changed into：
Further, cutting processing includes in the step 4：When terrain slope is not easy to very much walking suddenly, then can cut
Break this paths.For example when the gradient is more than 60 °, then it can be calculated according to formula (6) along the threshold value of X-axis and Y-axis and beOr
Threshold value diagonally isWhen the weights of some arcs in directed networkses are more than the threshold value, then this arc is deleted；When certain
A little summits are in unsuitable waters, then delete the arc of these summits and its connection.
Further, it is using the detailed process of Dijsktra algorithms progress route searching in the step 5：
(5.1) the vertex set S={ V of initial season mark0, vertex set T=V-S=to be marked { remaining top
Point }, the distance value of vertex correspondence in T；If in the presence of<V0,Vi>, d (V0,Vi) be<V0,Vi>Weights on arc；If it is not present<V0,Vi
>, d (V0,Vi) it is infinity；
(5.2) the summit W of a side relevant with summit in S and weights minimum is chosen from T, is added in S to remaining T
The distance value on middle summit is modified：If adding W makees intermediate vertex, from V0To ViDistance value shorten, then change this distance value；
(5.3) repeat the above steps (5.2)-(5.3), until including all summits, i.e. W=V in SiUntill
Beneficial effect：Compared with prior art, the present invention has advantages below：
1st, the directed networkses path method for solving proposed by the present invention towards landform path planning, with reference to digital Terrain Analysis
DEM specifications Grid square represent field model, on the basis of based on graph theory, build directed networkses, be landform path planning with
It is basic using establishing.
2nd, the optimum path planning method proposed by the present invention based on directed networkses, to take the shortest path of features of terrain into account
Optimization Modeling and quick calculate, there is provided new approach.
3rd, present invention is fully applicable to the most short based on directed networkses of the terrain analysis field of extensive mass data
In terms of the quick calculating of path planning, for example, tourism path planning, hazardous materials transportation path planning based on recallable amounts,
The hidden path planning of army's march, landscape Analysis and assessment, military, spatial cognition and decision-making, archaeology etc. can also be applied to and led
The application scenarios such as the research meanses based on the recallable amounts in domain, improve treatment effeciency.
Brief description of the drawings
Fig. 1 is the directed networkses structure flow chart in embodiment；
Fig. 2 is the DEM grid adjacent modes figures in embodiment；
Fig. 3 is the weight computing schematic diagram on 4 grid adjacent unit pattern directed networkses sides in embodiment；
Fig. 4 is the weight computing schematic diagram on 8 grid adjacent unit pattern directed networkses sides in embodiment.
Wherein, Fig. 2 (a) is 4 grid unit pattern diagrams；Fig. 2 (b) is 8 grid unit pattern diagrams.
Embodiment
Technical solution of the present invention is described in detail below, but protection scope of the present invention is not limited to the implementation
Example.
As shown in figure 1, a kind of landform paths planning method based on directed networkses of the present invention, comprises the following steps：
Step 1, dem data initializes：DEM grid altitude datas are scanned according to required precision, analysed whether
Empty data on some grid units be present, if in the presence of execution interpolation calculation obtains the altitude data of the unit；
Step 2, neighbouring computation schema is selected：According to route searching required precision, the grid list of selection structure directed networkses
The neighbouring computation schema of member, this includes 4 grid unit adjacent modes (precision is low) adjacent to computation schema type and 8 grid units are neighbouring
Pattern (precision is high)；
Step 3, the weights of the arc that summit is connected in directed networkses are calculated：According to the adjacent modes of selection, calculate oriented
The weights of connection arc in network between every opposite vertexes, and then obtain the directed networkses of primary；
Step 4, directed networkses are cut：According to the constraint requirements of landform route, delete respective vertices in directed networkses and
Connection arc between summit；Final directed networkses are can obtain by beta pruning processing；
Step 5, optimum path planning：The directed networkses obtained based on step 4, path is carried out using Dijsktra algorithms and searched
Rope, starting point and terminal according to path obtain global optimum's traffic path.Detailed process is：(1) initial season mark
Vertex set S={ V0, the distance value of vertex correspondence in vertex set T=V-S=to be marked { remaining summit }, T；If deposit
<V0,Vi>, d (V0,Vi) be<V0,Vi>Weights on arc；If it is not present<V0,Vi>, d (V0,Vi) it is infinity；(2) from T
The summit W of a side relevant with summit in S and weights minimum is chosen, is added in S and the distance value on summit in remaining T is carried out
Modification：If adding W makees intermediate vertex, from V0To ViDistance value shorten, then change this distance value；(3) repeat the above steps (2)-
(3), until including all summits, i.e. W=V in SiUntill.
When the weights of all arcs in directed networkses are calculated in above-mentioned steps 3, according to the required precision of path planning, it may be selected
4 grid adjacent modes or 8 grid adjacent modes carry out the weight computing formula of arc, and calculate the weights size of arc：
Based on 4 grid unit adjacent modes, referring to Fig. 2 (a), it is considered as grid unit and is connected along 4 directions of reference axis,
That is grid center is to 1,2,3 and 4 grid points.The weight computing on the side of its figure network model is fairly simple, its geometric representation such as Fig. 3
It is shown.
Assuming that grid unit ViAnd VjHeight value be respectively EiAnd Ej, along a length of a of X-axis between grid, along a length of b of Y-axis, then
The weight computing formula on the side of figure network is as follows：
If grid is square, i.e. a=b=d, then formula (1) is changed into：
If being normalized, formula (2) is changed into：
Based on 8 grid unit patterns, referring to Fig. 2 b), (1,2,3 and 4 point), also edge in addition to 4 directions along reference axis
Cornerwise 4 directions (5,6,7 and 8 points).The weight calculation method on the side of its directed networks is as shown in Figure 4.Assuming that grid list
First ViAnd VjHeight value be respectively EiAnd Ej, along a length of a of X-axis between grid, along a length of b of Y-axis, then the weights on the side of directed networkses
For：
If square grid, i.e. a=b=d, then formula (4) is changed into：
It is normalized, then formula (5) is changed into：
Further, cutting processing includes in the step 4：When terrain slope is not easy to very much walking suddenly, then threshold is set
Value；When the weights of some arcs in directed networkses are more than the threshold value, then this arc is deleted；When some summits are in unsuitable water
Domain, then delete the arc of these summits and its connection.
Directed networkses are the figure method for expressing in a kind of graph theory, and the height value of topographic(al) point on regular grid is transformed into use
The directed networkses that summit and arc represent, new way is provided for Optimization Modeling.
In specific path planning, objective optimization model, such as shortest path, most I can be established according to directed networkses
Apparent path etc..In siteselecting planning, model and its algorithm in the maximum visual domain based on directed networkses etc. can be established.
It can be seen from above-described embodiment that digital elevation model is converted into directed networkses by the present invention, then oriented
Path planning can is carried out in network and carries out Shortest Path Searching using about the algorithm in graph theory.Militarily, Ke Yitong
Cross directed networkses and find most hidden path.In path planning of travelling, directed networkses can be utilized to find minimal path and observation
To most sight spots.In hazardous materials transportation route planning, be exactly on the basis of directed networkses find it is one most short and dangerous
The route for the harm minimum that product are revealed or blast is caused.
Claims (4)
- A kind of 1. landform paths planning method based on directed networkses, it is characterised in that：Comprise the following steps：Step 1, dem data initializes：DEM grid altitude datas are scanned according to required precision, analysed whether some Empty data on grid unit be present, if in the presence of execution interpolation calculation obtains the altitude data of the unit；Step 2, neighbouring computation schema is selected：According to route searching required precision, the grid unit of selection structure directed networkses is adjacent Nearly computation schema, this includes 4 grid unit adjacent modes and 8 grid unit adjacent modes adjacent to computation schema type；Step 3, the weights of the arc that summit is connected in directed networkses are calculated：According to the adjacent modes of selection, directed networkses are calculated In weights per the connection arc between opposite vertexes, and then obtain the directed networkses of primary；Step 4, directed networkses are cut：According to the constraint requirements of landform route, the respective vertices in directed networkses and summit are deleted Between connection arc；Final directed networkses are can obtain by beta pruning processing；Step 5, optimum path planning：The directed networkses obtained based on step 4, route searching is carried out using Dijsktra algorithms, Starting point and terminal according to path obtain global optimum's traffic path.
- 2. the landform paths planning method according to claim 1 based on directed networkses, it is characterised in that：The step 3 The method of middle weight computing is：When computation schema is based on 4 grid unit adjacent modes, grid unit is regarded as along 4 direction connections of reference axis, if Any grid points V in landformiAnd VjHeight value be respectively EiAnd Ej, it is along a length of b of Y-axis, then oriented along a length of a of X-axis between grid The weight computing formula on the side of network is as follows：Here, ViAnd VjIt is the grid unit point in landform, EiAnd EjV is corresponded to respectivelyiAnd VjHeight value, and a and b difference It is the length of side of rectangle grid unit；If grid unit is square, if the length of side of square is d, i.e. a=b=d, then formula (1) is changed into：<mrow> <msub> <mi>L</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>=</mo> <msqrt> <mrow> <msup> <mi>d</mi> <mn>2</mn> </msup> <mo>+</mo> <msup> <mrow> <mo>(</mo> <msub> <mi>E</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>E</mi> <mi>j</mi> </msub> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </msqrt> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>If being normalized, formula (2) is changed into：<mrow> <msub> <mi>l</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>=</mo> <mfrac> <msub> <mi>L</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mi>d</mi> </mfrac> <mo>=</mo> <msqrt> <mrow> <mn>1</mn> <mo>+</mo> <msup> <mrow> <mo>(</mo> <mfrac> <mrow> <msub> <mi>E</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>E</mi> <mi>j</mi> </msub> </mrow> <mi>d</mi> </mfrac> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </msqrt> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow>When computation schema is based on 8 grid unit pattern, grid unit is regarded as in addition to 4 directions along reference axis also along right 4 directions connection of linea angulata, it is assumed that grid unit ViAnd VjHeight value be respectively EiAnd Ej, along a length of a of X-axis between grid, along Y Axial length is b, then the weights on the side of directed networkses are：If square grid, i.e. a=b=d, then formula (4) is changed into：It is normalized, then formula (5) is changed into：
- 3. the landform paths planning method according to claim 1 based on directed networkses, it is characterised in that：The step 4 Middle cutting processing includes：When terrain slope is not easy to very much walking suddenly, then threshold value is set；When the weights of some arcs in directed networkses More than the threshold value, then this arc is deleted；When some summits are in unsuitable waters, then these summits and its connection are deleted Arc.
- 4. the landform paths planning method according to claim 1 based on directed networkses, it is characterised in that：The step 5 It is middle using Dijsktra algorithms carry out route searching detailed process be：(5.1) the vertex set S={ V of initial season mark0, in vertex set T=V-S=to be marked { remaining summit }, T The distance value of vertex correspondence；If in the presence of<V0,Vi>, d (V0,Vi) be<V0,Vi>Weights on arc；If it is not present<V0,Vi>, d (V0, Vi) it is infinity；(5.2) the summit W of a side relevant with summit in S and weights minimum is chosen from T, is added in S to being pushed up in remaining T The distance value of point is modified：If adding W makees intermediate vertex, from V0To ViDistance value shorten, then change this distance value；(5.3) repeat the above steps (5.2)-(5.3), until including all summits, i.e. W=V in SiUntill.
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| CN111504322B (en) * | 2020-04-21 | 2021-09-03 | 南京师范大学 | Scenic spot tour micro-route planning method based on visible field |
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