CN114562998A

CN114562998A - Multi-target-point path planning method based on DEM (digital elevation model) under non-road condition in mountainous area

Info

Publication number: CN114562998A
Application number: CN202210116041.1A
Authority: CN
Inventors: 戴龙; 卢欲鸿; 孙帅旗; 郁文赫; 陈淑迎; 杨阳; 姚勇航
Original assignee: Beijing Sixiang Aishu Technology Co ltd
Current assignee: Beijing Sixiang Aishu Technology Co ltd
Priority date: 2022-01-27
Filing date: 2022-01-27
Publication date: 2022-05-31

Abstract

The invention provides a multi-target point path planning method under the condition of no road in a mountainous area based on a DEM (digital elevation model), belonging to the field of motion control; the method specifically comprises the following steps: firstly, selecting DEM data from a geographic space data cloud, and calculating and generating gradient raster data; and resampling the gradient raster data to obtain cost raster data. Then, the starting point and a plurality of rescue points are combined at the user side and used as the parameter input of the connectivity analysis. And then, calculating the connectivity of the initial point and the rescue point by using the input parameters and the cost raster data to obtain a communication path and a cost distance between the data, and forming a communication network topological graph between the merging points. Finally, referring to a connected network topological graph, and generating a shortest path from a starting point to a plurality of rescue points by using a TSP problem solution algorithm; and presented to the user. The invention solves the problem of path planning from one point to a plurality of target points in mountainous areas without roads and is realized in an engineering way.

Description

Multi-target-point path planning method based on DEM (digital elevation model) under non-road condition in mountainous area

Technical Field

The invention relates to the field of motion control, in particular to a path planning method of multiple target points under a mountainous area road-free condition based on a DEM (digital elevation model).

Background

The mountainous area battlefield environment is complex, the fighters are highly centralized, a large number of wounded persons occur, the wounded situations are complex, the medical treatment difficulty is high, and the medical treatment which is efficient and accurate at the first time has important significance for saving precious lives of the wounded persons, reducing the disability rate and the casualty rate of the army and ensuring that the fighting will of the army continuously rises.

Therefore, in the rescue plan of the wounded in the battlefield, scientific management is carried out, emergency rescue is carried out according to emergency flow allocation and personnel division, and the wounded are organized and arranged.

For battlefield emergency search and rescue, particularly hiking search and rescue work, how to find the shortest path plays a very important guiding role in the rescue task.

The shortest search path is the best path from the starting point to the end point, and the shortest path algorithm which is most commonly used in practical application, such as Dijkstra algorithm, searches the shortest paths of all path nodes from the starting point until the end point is found. However, this algorithm is inefficient in operation when the amount of data is large.

The path planning method has more researches in the field of urban emergency rescue, and aims at multipoint rescue planning, a genetic algorithm and a linear planning method are combined, and an optimal path is found out from a specific line and a node by using the combination of a plurality of line segments in the existing vector diagram. Based on raster data, corresponding algorithms can search the optimal path between target points, for example, ArcGIS and SuperMap also have corresponding algorithm integration.

However, the traditional path planning application scenario is performed under the condition that urban roads are relatively complete, the accessibility of rescuers is extremely poor in high-altitude mountain areas without road networks, and the traditional shortest path planning method based on the vector road network lacks necessary data bases and cannot meet the implementation under the condition without road. Although based on raster data, the ArcGIS CostConnectivity toolkit can compute connectivity between different points; however, the comprehensive shortest path from the starting point to the multiple target points cannot be calculated, and the rescue problem from the starting point to the multiple target points cannot be solved.

Disclosure of Invention

Aiming at the problems, the invention provides a multi-target-point path planning method under the condition of no road in a mountainous area based on DEM, and solves the command and scheduling problems of battlefield environment emergency rescue under the condition of no road in complex terrain.

The path planning method for multiple target points under the condition of no road in mountainous areas based on DEM comprises the following specific steps:

the method comprises the steps that firstly, DEM data are selected from geospatial data cloud, and gradient raster data are calculated and generated;

and step two, resampling the generated gradient raster data to obtain cost raster data.

And step three, combining the starting point and the plurality of rescue points at the user side to be used as parameter input of connectivity analysis.

After combination, there is a unique ID number field to record the starting point and the ending point.

And step four, calculating the connectivity of the initial point and the rescue point by using the input parameters and the cost raster data to obtain a communication path and a cost distance between the data, and forming a communication network topological graph between the merging points.

The connected network topological graph is a two-dimensional table and comprises each record as an edge, two nodes REGION1 and REGION2 of each edge and the weight PATHCOST of the edge;

where nodes REGION1 and REGION2 are the unique ID number fields for the starting point and rescue point, respectively.

Step five, generating a shortest path from a starting point to a plurality of rescue points by referring to a connected network topological graph and utilizing a TSP problem solving algorithm; and presented to the user.

The invention has the advantages that:

the invention relates to a path planning method for multiple target points under a mountainous area road-free condition based on a DEM (digital elevation model), which solves the problem of path planning from one point to multiple target points under the mountainous area road-free condition and is realized in an engineering way.

Drawings

FIG. 1 is a schematic diagram of a path planning method for multiple target points under a mountainous area road-free condition based on DEM (digital elevation model);

FIG. 2 is a flow chart of a multi-target point path planning method based on DEM under the condition of no road in a mountain area according to the invention;

FIG. 3 is an exemplary diagram of a cost grid according to the present invention;

FIG. 4 is a topological diagram of a multi-target emergency rescue adjacent connected network formed by the invention;

fig. 5 is a diagram of the optimal path planning result for multi-objective emergency rescue according to the present invention.

Detailed Description

The present invention will be described in further detail with reference to the following examples and the accompanying drawings.

The invention relates to a multi-target point path planning method under a mountainous area road-free condition based on DEM (digital elevation model). As shown in figure 1, firstly, ASTER GDEM 30M DEM data is selected from a standard database disclosed in a global scope to generate gradient data, and then a cost grid is obtained through resampling; then, inputting a starting point and combining a plurality of rescue points through a user side to obtain a combined point; combining the merging points and the cost grids into a connected network topological graph through connectivity calculation; and finally, outputting an optimal path planning result through TSP calculation.

As shown in fig. 2, the specific steps are as follows:

selecting DEM data from a geographic space data cloud, and calculating to generate gradient data;

DEM data is derived from ASTER GDEM 30M resolution provided by a geospatial data cloud (http:// www.gscloud.cn /).

And step two, resampling the generated gradient data, wherein a resampling mapping table is shown in table 1, and obtaining cost grid data.

The reason for using grade data as a cost grid is to consider that the greatest resistance of rescue forces while traversing a path is derived from grade. In actual operation, if a starting point and a plurality of rescue point ranges can be predicted, cost grids within the range can be calculated.

TABLE 1

Cost grid example figure as shown in figure 3, the darker the color, the lower the cost, the higher the color, the lower the cost grid is a grid of data used to calculate spatial impedance weights for spatial distances. The gradient data can be generated by different methods, the gradient data is mainly adopted in the method, and similarly, other data such as: and (4) using the land use type and the like as data sources, and generating a new cost grid through superposition of a certain weight ratio.

And step three, inputting a starting point and a plurality of rescue points at the user side to be merged as the parameter input of connectivity analysis.

And step four, calculating the connectivity of the initial point and the rescue point by using the input parameters and the cost raster data to obtain a communication path and a cost distance between the merging point data to form a communication network topological graph between the merging points.

Calculating connectivity using an analysis method (ArcGIS CostConnectivity) of commercial software;

the connected network topological graph is a two-dimensional table, and the attribute table is shown in table 1; including each record as an edge, two nodes REGION1 and REGION2 for each edge, and the weight of the edge, path pos;

TABLE 1

The map representation corresponding to this table is shown in fig. 4.

Step five, referring to a connected network topological graph, and generating a shortest path from a starting point to a plurality of rescue points by using a TSP (tracking Salesman Problem) problem solving algorithm; and presented to the user.

As shown in fig. 5, that is, the shortest path finally generated between the starting point and the rescue point.

Claims

1. A multi-target point path planning method based on DEM under the condition of no road in a mountain area is characterized by comprising the following specific steps:

Firstly, selecting DEM data from a geographic space data cloud, and calculating to generate gradient raster data; resampling the generated gradient raster data to obtain cost raster data;

then, combining the starting point and a plurality of rescue points at the user side, and respectively recording the starting point and the ending point by using a unique ID number field as parameter input of connectivity analysis;

then, calculating the connectivity of the initial point and the rescue point by using the input parameters and the cost raster data to obtain a communication path and a cost distance between the data to form a communication network topological graph between the merging points;

finally, referring to a connected network topological graph, and generating a shortest path from a starting point to a plurality of rescue points by using a TSP problem solution algorithm; and presented to the user.

2. The DEM-based path planning method for multiple target points in a mountainous area without roads condition as claimed in claim 1, wherein the connected network topology is a two-dimensional table including one edge for each record, two nodes REGION1 and REGION2 for each edge, and a weight of the edge, path qos;