CN113984062A - Ground vehicle path planning method based on mobility evaluation - Google Patents

Ground vehicle path planning method based on mobility evaluation Download PDF

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CN113984062A
CN113984062A CN202111250187.7A CN202111250187A CN113984062A CN 113984062 A CN113984062 A CN 113984062A CN 202111250187 A CN202111250187 A CN 202111250187A CN 113984062 A CN113984062 A CN 113984062A
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cost
vehicle
mobility
soil
terrain
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CN113984062B (en
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牛润新
华琛
余彪
郑小坤
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Hefei Institutes of Physical Science of CAS
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes

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Abstract

The invention discloses a ground vehicle path planning method based on mobility evaluation, which comprises the steps of obtaining multi-source data, utilizing a land statistics method to carry out terrain and environment three-dimensional reconstruction, and obtaining a three-dimensional point cloud terrain model, wherein the multi-source data comprises remote sensing elevation terrain data, land utilization data, soil type distribution data and vehicle data; according to the terrain factors, the trafficability analysis and the mobility cost quantification of the ground mechanics effect, the mobility of the vehicle in the traffic area is evaluated; and (4) performing path planning by adopting a cost function of the improved A-Star algorithm. According to the method, a three-dimensional point cloud terrain model is reconstructed by acquiring multi-source data, vehicle mobility evaluation is carried out after analysis of terrain and soil data, and finally an optimally planned path is acquired according to an improved A-Star algorithm. The problem of lack of path planning technology of special operation vehicles in the field environment without a road network is solved. The visual three-dimensional visual display is provided, and a decision maker is assisted in analyzing and optimizing after planning a path.

Description

Ground vehicle path planning method based on mobility evaluation
Technical Field
The invention relates to the technical field of vehicle path planning, in particular to a ground vehicle path planning method based on mobility evaluation.
Background
At present, with the acceleration of urban development, a digital map technology for an urban road network is quite mature, and vehicles can carry out effective path planning between a starting point and a target according to a specific urban scene. However, in a field environment without a road network, the path planning technology for a special operation vehicle is deficient, for example, in the military field, a military vehicle can meet various unknown complex ground environments in the field, and in order to guarantee military tactical maneuverability, the maneuverability of the vehicle in the area is firstly evaluated and the path planning is carried out. The maneuverability of a vehicle is influenced by factors such as terrain, soil, and parameters of the vehicle, so that the assessment of the maneuverability of the vehicle is a result of complex multi-factor coupling.
The current mobility evaluation method is usually to evaluate the passing performance of a vehicle and divide a terrain into a passable area and a non-passable area, however, for a task decision maker, it is difficult to discriminate a more optimal area suitable for the vehicle to run from the passable area, so that the mobility of the vehicle needs to be quantified for the passable area, meanwhile, when the passable area and the non-passable area are judged, the influence of a soil mechanical effect on the mobility of the vehicle is not considered, different soil types not only restrict whether the vehicle can pass, but also restrict the speed of the vehicle due to the soil mechanical effect, and therefore, when the mobility of the vehicle on a certain terrain is quantified, the influence of the soil mechanical effect on the mobility of the vehicle needs to be considered. In the path planning process, only factors such as the distance between a starting point and a target point and the terrain cost are considered, the number of uphill times of a vehicle, the accumulated length of the uphill and the road curvature are not considered, and based on the path planning result of the two-dimensional grid, the intuitive three-dimensional visual display is difficult to carry out, the fluctuation of the terrain is observed by a task decision maker, whether the generated path meets the task requirement or not is analyzed, and the subsequent path optimization causes certain difficulty.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and in order to realize the purpose, a ground vehicle path planning method based on mobility evaluation is adopted to solve the problems in the background technology.
A ground vehicle path planning method based on mobility assessment comprises the following steps:
acquiring multi-source data, and performing terrain and environment three-dimensional reconstruction by using a land statistical method to obtain a three-dimensional point cloud terrain model, wherein the multi-source data comprises remote sensing elevation terrain data, land utilization data, soil type distribution data and vehicle data of a traffic area;
according to the terrain factors, the trafficability analysis and the mobility cost quantification of the ground mechanics effect, the mobility of the vehicle in the traffic area is evaluated;
and (4) performing path planning by adopting a cost function of the improved A-Star algorithm.
As a further aspect of the invention: the specific steps of obtaining multi-source data and utilizing a geostatistical method to carry out terrain and environment three-dimensional reconstruction comprise:
converting remote sensing elevation terrain data into point cloud, and establishing a three-dimensional terrain point cloud model;
refining the terrain point cloud resolution by using a kriging interpolation method, and calculating the gradient value of each point;
and projecting the land utilization data and the soil type distribution data onto corresponding geographical points, wherein the soil type distribution data comprise soil types, soil strength values and mechanical parameters influencing the mobility of the vehicle.
As a further aspect of the invention: the specific steps of the passing analysis comprise:
the method comprises the following steps: obtaining the gradient value beta of each point according to calculationiDefinition of
Figure BDA0003322207670000021
Is an impassable point, otherwise is a passable point, wherein
Figure BDA0003322207670000022
Is the threshold value of the roll angle of the vehicle,
Figure BDA0003322207670000023
is a threshold for pitch angle.
Step two: defining an impassable area and a passable area according to the land utilization data;
step three: calculating a vehicle mobility index MI according to the vehicle data, wherein the mobility index calculation formula is as follows:
Figure BDA0003322207670000024
in the formula, PFGThe ground contact pressure coefficient, the weight coefficient, the tire coefficient, the wheel prick coefficient, the wheel load coefficient, the ground clearance coefficient, the engine coefficient and the transmission coefficient are respectively represented as W, T, G, L, E and X;
obtaining a minimum soil strength value VCI which can be passed by a vehicle according to the vehicle mobility index, wherein the calculation formula of the minimum soil strength value VCI is as follows: VCI 25.5+0.456 MI;
judging the size of the soil according to the minimum soil strength value VCI and the soil strength value CI, wherein if the VCI is larger than the CI, vehicles can pass through different soil types, and otherwise, vehicles cannot pass through the soil types;
step four: and marking the passable points and the impassable points according to the result of the trafficability analysis, and simultaneously generating passable and impassable maps.
As a further aspect of the invention: the specific steps of the mobility cost quantification include:
the method comprises the following steps: calculating the running resistance on soil types with different strengths according to different modes of the vehicle tire, wherein the wheel modes comprise an elastic wheel mode and a rigid wheel mode;
when the vehicle runs in the rigid wheel mode, the running resistance calculation formula is as follows:
Frc＝(3W)(2n+2)/(2n+1)/(3-n)(2n+2)/(2n+1)(n+1)(kc+bkφ)1/(2n+1)D(n+1)/(2n+1)；
when the vehicle runs in the elastic wheel mode, the running resistance calculation formula is as follows:
Frc＝(W/L)(n+1)/n1/(n+1)(kc+bkφ)1/n；
in the formula, FrcFor the running resistance of the vehicle on the soil, kcModulus of deformation for soil cohesion, kφThe method comprises the following steps of (1) taking the internal friction deformation modulus of soil, n being a soil deformation index, W being a vertical load on a wheel, b being the width of a tire, D being the diameter of the wheel, and L being the projection length of the flattened tire;
step two: according to the calculation of the running resistance F in different modesrcAnd slope generated ramp resistance FsRated power P of the vehicleeCalculating the maximum speed V that can be reachedMAXThe calculation formula is as follows: vMAX＝Pe/(Frc+Fs)；
Step three: according to the elevation value, the gradient value, the soil strength value and the maximum possible speed of the vehicle at each topographic point, carrying out normalization processing to obtain the elevation cost of each topographic point
Figure BDA0003322207670000031
Cost of grade
Figure BDA0003322207670000032
Cost of soil strength
Figure BDA0003322207670000033
Maximum possible speed cost
Figure BDA0003322207670000034
And then obtaining the mobility Cost value Cost of each topographic point according to the weight superposition Cost value, wherein the expression is as follows:
Figure BDA0003322207670000035
in the formula, ω1+ω2+ω3+ω4＝1、ω1Weight value, omega, at the cost of gradient2Weight value, omega, for soil strength cost3Weight value at the maximum possible speed cost,ω4A weight value at an elevation cost;
step four: obtaining standard deviation sigma of each item costiAnd average value
Figure BDA0003322207670000038
Calculating the coefficient of variation gamma of each costi：
Figure BDA0003322207670000036
And determining the weight value omega of each cost according to the ratio of the variation coefficients of the costsi(i ═ 1,2,3,4), the calculation formula is:
Figure BDA0003322207670000037
and the cost value of the impassable point is set as 1;
step five: and traversing all terrain points according to the steps to establish a visualized vehicle mobility distribution map, wherein the mobility of the vehicle on the terrain is reflected by using numerical values, and the numerical values are closer to 1, the lower the mobility of the vehicle is represented, the closer to 0, the higher the mobility of the vehicle is represented.
As a further aspect of the invention: the specific steps of planning the path by adopting the cost function of the improved A-Star algorithm comprise:
obtaining parameters of a cost function, including mobility cost, uphill times, accumulated uphill distance, path curvature and distance, wherein the formula of the cost function is as follows:
Figure BDA0003322207670000041
in the formula, CiAt a cost of mobility, NiFor accumulating the cost of ascending times, LiFor accumulating the cost of uphill distance, PiAs the cost of path curvature, ωa、ωb、ωc、ωdRespectively is the weight value of each cost;
the method is used for reducing the traversal number of the algorithm by presetting the high-mobility cost points and the non-passable points, and adjusting and optimizing according to the path planning result.
Compared with the prior art, the invention has the following technical effects:
by adopting the technical scheme, the landform and the environment are reconstructed by utilizing the acquired multi-source data and a ground statistical method, and a three-dimensional landform point cloud model is established. And then remote sensing elevation terrain data, land utilization data, soil type distribution data and vehicle data in the obtained multi-source data are utilized to carry out vehicle trafficability analysis and mobility cost quantification. And finally, planning the path according to the improved A-Star algorithm to obtain the optimal path. By the path planning method, the problem that the path planning technology for special operation vehicles is deficient in the field environment without a road network is solved, and the maneuverability of the vehicles meeting various unknown complex ground environments in the field is guaranteed.
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The following detailed description of embodiments of the invention refers to the accompanying drawings in which:
FIG. 1 is a schematic illustration of steps of a ground vehicle path planning method according to some embodiments disclosed herein;
FIG. 2 is a schematic diagram of a conversion of remote sensing terrain elevation data into a three-dimensional terrain point cloud model according to some embodiments of the present disclosure;
FIG. 3 is a schematic diagram of a 3 × 3 moving window slope value calculation method according to some embodiments disclosed herein;
FIG. 4 is a schematic view of a wheel driving condition on different soils according to some embodiments of the present disclosure;
FIG. 5 is a schematic view of passable and impassable three-dimensional terrain point cloud models of some embodiments disclosed herein;
FIG. 6 is a three-dimensional representation of vehicle mobility penalty for some embodiments disclosed herein;
FIG. 7 is a schematic diagram of path curvature calculation for some embodiments disclosed herein;
FIG. 8 is a schematic flow chart of the A-Star algorithm of some embodiments disclosed herein;
FIG. 9 is a three-dimensional schematic view of a vehicle path plan of some embodiments disclosed herein;
fig. 10 is a schematic top view of a vehicle path plan in accordance with some embodiments disclosed herein.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, in an embodiment of the present invention, a method for planning a path of a ground vehicle based on mobility evaluation includes:
s1, acquiring multi-source data and performing terrain and environment three-dimensional reconstruction by using a ground statistical method to obtain a three-dimensional point cloud terrain model, wherein the multi-source data comprises remote sensing elevation terrain data, land utilization data, soil type distribution data and vehicle data of an acquired traffic area;
in a specific embodiment, the specific steps of obtaining multi-source data and performing three-dimensional reconstruction of terrain and environment by using a geostatistical method include:
s11, converting the remote sensing elevation terrain data into point clouds, and establishing a three-dimensional terrain point cloud model;
specifically, as shown in fig. 2, a certain interested real field terrain is selected, and elevation data of the terrain with low resolution in the area is acquired from a geographic information system; converting the land utilization data and the soil type distribution data of the area into point data, and exporting text files in the form of x, y and z three-dimensional coordinates; and importing the three-dimensional coordinate text file of the terrain into Matlab software to generate a visualized three-dimensional point cloud terrain model.
S12, refining the terrain point cloud resolution by using a Krigin interpolation method, and calculating the gradient value of each point;
specifically, the terrain elevation data is reconstructed by a kriging interpolation method based on spatial autocorrelation to generate a three-dimensional point cloud terrain model with the resolution ratio d.
And projecting the land utilization data and the soil type distribution data onto corresponding geographical points, wherein the soil type distribution data comprise soil types, soil strength values and mechanical parameters influencing the mobility of the vehicle.
S13, calculating the gradient value of each point in the data according to the three-dimensional point cloud terrain model obtained by interpolation, as shown in figure 3, traversing the whole three-dimensional point cloud by adopting a 3 multiplied by 3 moving window, and calculating the gradient value beta of each pointiSlope value beta of each pointiThe calculation formula of (2) is as follows:
Figure BDA0003322207670000061
wherein S isL＝[(h8+2h1+h5)-(h7+2h3+h6)]|/(8×d)；
ST＝[(h7+2h4+h8)-(h6+2h2+h5)]|/(8×d)；
In the formula, hiD is the resolution.
S2, evaluating the vehicle mobility of the passing area according to the trafficability analysis and mobility cost quantification of the terrain factors and the ground mechanics effect;
in a specific embodiment, the specific steps of the passability analysis include:
s21, obtaining the gradient value beta of each point according to the calculationiDefinition of
Figure BDA0003322207670000062
Is an impassable point, otherwise is a passable point, wherein
Figure BDA0003322207670000063
Is the threshold value of the roll angle of the vehicle,
Figure BDA0003322207670000064
is a threshold for pitch angle.
S22, defining an impassable area and a passable area according to the land utilization data;
specifically, points covered by the forest land and the water body area are defined as impassable points, and points covered by the agricultural land, the grassland and the sand land are defined as passable points according to land utilization data provided by the geographic national condition monitoring cloud platform.
S23, calculating a vehicle mobility index MI according to the vehicle data, specifically, according to the soil type distribution data, defining the cone index CI of different soil types as the strength value of the soil, and combining the parameters of the target vehicle, wherein the specific parameters include a ground pressure coefficient PFGThe weight coefficient W, the tire coefficient T, the wheel prick coefficient G, the wheel load coefficient L, the ground clearance coefficient H, the engine coefficient E and the transmission coefficient X, so as to calculate the vehicle mobility index MI;
the mobility index calculation formula is as follows:
Figure BDA0003322207670000065
in the formula, PFGThe ground contact pressure coefficient, the weight coefficient, the tire coefficient, the wheel prick coefficient, the wheel load coefficient, the ground clearance coefficient, the engine coefficient and the transmission coefficient are respectively represented as W, T, G, L, E and X;
obtaining a minimum soil strength value VCI which can be passed by a vehicle according to the vehicle mobility index, wherein the calculation formula of the minimum soil strength value VCI is as follows: VCI 25.5+0.456 MI;
judging the size of the soil according to the minimum soil strength value VCI and the soil strength value CI, wherein if the VCI is larger than the CI, vehicles can pass through different soil types, and otherwise, vehicles cannot pass through the soil types;
and S24, marking the passable points and the impassable points according to the result of the trafficability analysis, and simultaneously generating passable and impassable maps. Specifically, as shown in fig. 4, the passable point is marked as GO, and the unviable point is marked as NOGO.
In a specific embodiment, the step of quantifying the mobility cost includes:
s25, calculating the running resistance on the soil types with different strengths according to different modes of the vehicle tires, as shown in figure 5, wherein the wheel modes comprise an elastic wheel mode and a rigid wheel mode;
when the vehicle runs in the rigid wheel mode, the running resistance calculation formula is as follows:
Frc＝(3W)(2n+2)/(2n+1)/(3-n)(2n+2)/(2n+1)(n+1)(kc+bkφ)1/(2n+1)D(n+1)/(2n+1)；
when the vehicle runs in the elastic wheel mode, the running resistance calculation formula is as follows:
Frc＝(W/L)(n+1)/n1/(n+1)(kc+bkφ)1/n；
in the formula, FrcFor the running resistance of the vehicle on the soil, kcModulus of deformation for soil cohesion, kφThe method comprises the following steps of (1) taking the internal friction deformation modulus of soil, n being a soil deformation index, W being a vertical load on a wheel, b being the width of a tire, D being the diameter of the wheel, and L being the projection length of the flattened tire;
s26, calculating the running resistance F in different modesrcAnd slope generated ramp resistance FsSpecifically, the ramp resistance formula is: fsRated power P of vehicleeCalculating the maximum speed V that can be reachedMAXThe calculation formula is as follows: vMAX＝Pe/(Frc+Fs)；
S27, carrying out normalization processing according to the elevation value, the gradient value, the soil strength value and the maximum possible speed of the vehicle at each topographic point to obtain the elevation cost of each topographic point
Figure BDA0003322207670000071
Cost of grade
Figure BDA0003322207670000072
Cost of soil strength
Figure BDA0003322207670000073
Maximum possible speed cost
Figure BDA0003322207670000074
In particular, according to the elevation h of the pointiHighest height h in all passable pointsmaxAnd a minimum value hminAccording to the formula
Figure BDA0003322207670000081
Obtain its elevation cost
Figure BDA0003322207670000082
According to the slope value S of the pointiMaximum value of slope S in all passable pointsmaxAnd minimum value SminAccording to the formula
Figure BDA0003322207670000083
Obtain the gradient cost thereof
Figure BDA0003322207670000084
According to the soil intensity value CI of the pointiMaximum value CI of soil strength in all passable pointsmaxSum minimum CIminAccording to the formula
Figure BDA0003322207670000085
Obtaining the soil strength
Figure BDA0003322207670000086
According to the maximum possible speed V of the vehicle at that pointiMaximum value of speed V among all passable pointsmaxAnd a minimum value VminAccording to the formula
Figure BDA0003322207670000087
Obtain its speed cost
Figure BDA0003322207670000088
Traversing all passable points according to the process to obtain each Cost value of each point, and then obtaining the mobility Cost value Cost of each topographic point according to the weight superposition Cost value, wherein the expression is as follows:
Figure BDA0003322207670000089
in the formula, ω1+ω2+ω3+ω4＝1、ω1Weight value, omega, at the cost of gradient2Weight value, omega, for soil strength cost3Weight value, ω, at maximum possible velocity penalty4A weight value at an elevation cost;
s28, obtaining standard deviation sigma of each item costiAnd average value
Figure BDA00033222076700000810
Calculating the coefficient of variation gamma of each costi：
Figure BDA00033222076700000811
Therefore, the influence of different dimensions of each cost is avoided being eliminated due to different dimensions of each cost;
and determining the weight value omega of each cost according to the ratio of the variation coefficients of the costsi(i ═ 1,2,3,4), the calculation formula is:
Figure BDA00033222076700000812
and the cost value of the impassable point is set as 1;
s29, traversing all the topographical points according to the above steps to create a visualized vehicle mobility distribution map, as shown in fig. 6, wherein the mobility of the vehicle on the topographical is reflected by a numerical value, the closer the numerical value is to 1, the lower the mobility of the vehicle is represented, the closer to 0, the higher the mobility of the vehicle is represented.
And S3, performing path planning by adopting the cost function of the improved A-Star algorithm. The method comprises the following specific steps:
s31, carrying out optimal path planning between the starting point and the target point based on the search process of the A-Star algorithm, specifically, considering the distance, the ascending times, the accumulated ascending length, the path curvature and the mobility cost value.
And S32, acquiring parameters of a cost function based on the mobility cost values of the vehicle at various geographical points, wherein the parameters comprise mobility cost, uphill times, accumulated uphill distance, path curvature and distance.
The formula of the cost function is:
Figure BDA0003322207670000091
in the formula, CiAt a cost of mobility, NiFor accumulating the cost of ascending times, LiFor accumulating the cost of uphill distance, PiAs the cost of path curvature, ωa、ωb、ωc、ωdRespectively is the weight value of each cost;
specifically, as shown in FIG. 7, CiThe mobility cost distance between the node i and the father node is represented by the following expression: ci＝b×d×(Costi-1+Costi) Where d is the resolution size, Costi-1，CostiNode i-1, respectively, the mobility penalty of node i, when node i-1 is adjacent to node i with unit resolution, b equals 1, when node i-1 is diagonally adjacent to node i,
Figure BDA0003322207670000092
Ninumber of climbs to generate a path for node i along the parent node to the starting position, Ni＝Count(hi-hi-1> 0), statistics are generated from node i, along parent node, to h in the initial state generation pathi-hi-1Number > 0. L isiFor the uphill length of the path that node i makes along the parent node to the start position,
Figure BDA0003322207670000093
wherein when h isi-hi-1And if the K is greater than 0, the K is 1, otherwise the K is 0. PiIs node i edgeThe maximum curvature of the path from the parent node to the start position,
Figure BDA0003322207670000094
wherein L isABIndicating the length of the path generated by node i from the parent node to the start state, and L is the generated path.
The heuristic function h (n) for the modified A-Star algorithm is: h (n) ═ DiWherein D isiIs the euclidean distance of node i to the end point.
Specifically, as shown in fig. 8, 9 and 10, a path from a starting point to a target point is calculated according to a search flow of the a-Star algorithm;
step 1: and searching from the starting point, continuously accessing 8 neighborhood nodes, storing accessed but not searched free nodes into an OPEN list OPEN, and storing searched nodes into a closed list CLOSE.
Step 2: and traversing the nodes in the list, and if the target point does not exist, entering Step3, otherwise, entering Step 7.
Step 3: and calculating a cost function value f of the node in the OPEN table according to the improved A-Star cost function, and setting the node with the minimum cost function value as the current processing node. And if the number of the nodes with the minimum cost function values is multiple, selecting the node which is added into the OPEN table at last as the current processing node. It is deleted from the OPEN table and then moved to the CLOSE table.
Step 4: and traversing the reachable nodes of the neighborhood of the current processing node 8, and ignoring the reachable nodes as NGGO nodes or nodes in a CLOSE table.
Step 5: and judging whether the 8 neighborhood reachable nodes are in the OPEN table.
Step 6: if not, adding the current processing node into the OPEN table, setting the current processing node as a parent node of the current processing node, and recording f, g and h of the current processing node. And if so, inquiring whether the g value from the current processing node to the 8 neighborhood nodes is smaller. If yes, setting the father node of the current processing node as the current processing node, recalculating g and f values, repeating the steps 4-6 until 8 adjacent reachable nodes of the current processing node are traversed, and returning to Step 2.
Step 7: searching a target point, and moving along the parent node to the starting point from the target point to obtain path output.
And S33, reducing the algorithm traversal quantity by presetting the high-mobility cost points and the non-passable points, and adjusting and optimizing according to the path planning result.
Specifically, a three-dimensional visual scene is generated according to the passable cost quantification result, and a decision maker can more intuitively evaluate the vehicle mobility in the area through the scene task; and according to task requirements, weight values with different costs are adjusted to generate paths, and a decision maker can analyze attribute values of all path nodes to adjust and compare the current path through storing path nodes.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents, which should be construed as being within the scope of the invention.

Claims (5)

1. A ground vehicle path planning method based on mobility assessment is characterized by comprising the following steps:
acquiring multi-source data, and performing terrain and environment three-dimensional reconstruction by using a land statistical method to obtain a three-dimensional point cloud terrain model, wherein the multi-source data comprises remote sensing elevation terrain data, land utilization data, soil type distribution data and vehicle data of a traffic area;
according to the terrain factors, the trafficability analysis and the mobility cost quantification of the ground mechanics effect, the mobility of the vehicle in the traffic area is evaluated;
and (4) performing path planning by adopting a cost function of the improved A-Star algorithm.
2. The mobility-assessment-based ground vehicle path planning method according to claim 1, wherein the specific steps of obtaining multi-source data and performing terrain and environment three-dimensional reconstruction by using a geostatistical method comprise:
converting remote sensing elevation terrain data into point cloud, and establishing a three-dimensional terrain point cloud model;
refining the terrain point cloud resolution by using a kriging interpolation method, and calculating the gradient value of each point;
and projecting the land utilization data and the soil type distribution data onto corresponding geographical points, wherein the soil type distribution data comprise soil types, soil strength values and mechanical parameters influencing the mobility of the vehicle.
3. The mobility-assessment-based ground vehicle path planning method according to claim 2, wherein the specific steps of the passing analysis include:
the method comprises the following steps: obtaining the gradient value beta of each point according to calculationiDefinition of
Figure FDA0003322207660000011
Is an impassable point, otherwise is a passable point, wherein
Figure FDA0003322207660000012
Is the threshold value of the roll angle of the vehicle,
Figure FDA0003322207660000013
a threshold value for pitch angle;
step two: defining an impassable area and a passable area according to the land utilization data;
step three: calculating a vehicle mobility index MI according to the vehicle data, wherein the mobility index calculation formula is as follows:
Figure FDA0003322207660000014
in the formula, PFGThe ground contact pressure coefficient, the weight coefficient, the tire coefficient, the wheel prick coefficient, the wheel load coefficient, the ground clearance coefficient, the engine coefficient and the transmission coefficient are respectively represented as W, T, G, L, E and X;
obtaining a minimum soil strength value VCI which can be passed by a vehicle according to the vehicle mobility index, wherein the calculation formula of the minimum soil strength value VCI is as follows: VCI 25.5+0.456 MI;
judging the size of the soil according to the minimum soil strength value VCI and the soil strength value CI, wherein if the VCI is larger than the CI, vehicles can pass through different soil types, and otherwise, vehicles cannot pass through the soil types;
step four: and marking the passable points and the impassable points according to the result of the trafficability analysis, and simultaneously generating passable and impassable maps.
4. The method for ground vehicle path planning based on mobility evaluation according to claim 2, wherein the mobility cost quantification comprises the following specific steps:
the method comprises the following steps: calculating the running resistance on soil types with different strengths according to different modes of the vehicle tire, wherein the wheel modes comprise an elastic wheel mode and a rigid wheel mode;
when the vehicle runs in the rigid wheel mode, the running resistance calculation formula is as follows:
Frc＝(3W)(2n+2)/(2n+1)/(3-n)(2n+2)/(2n+1)(n+1)(kc+bkφ)1/(2n+1)D(n+1)/(2n+1)；
when the vehicle runs in the elastic wheel mode, the running resistance calculation formula is as follows:
Frc＝(W/L)(n+1)/n1/(n+1)(kc+bkφ)1/n；
in the formula, FrcFor the running resistance of the vehicle on the soil, kcModulus of deformation for soil cohesion, kφThe method comprises the following steps of (1) taking the internal friction deformation modulus of soil, n being a soil deformation index, W being a vertical load on a wheel, b being the width of a tire, D being the diameter of the wheel, and L being the projection length of the flattened tire;
step two: according to the calculation of the running resistance F in different modesrcAnd slope generated ramp resistance FsRated power P of the vehicleeCalculating the maximum speed V that can be reachedMAXThe calculation formula is as follows: vMAX＝Pe/(Frc+Fs)；
Step three: according to the elevation value, the gradient value, the soil strength value and the maximum possible speed of the vehicle at each topographic point, carrying out normalization processing to obtain the elevation cost of each topographic point
Figure FDA0003322207660000023
Cost of grade
Figure FDA0003322207660000024
Cost of soil strength
Figure FDA0003322207660000025
Maximum possible speed cost
Figure FDA0003322207660000022
And then obtaining the mobility Cost value Cost of each topographic point according to the weight superposition Cost value, wherein the expression is as follows:
Figure FDA0003322207660000021
in the formula, ω1+ω2+ω3+ω4＝1、ω1Weight value, omega, at the cost of gradient2Weight value, omega, for soil strength cost3Weight value, ω, at maximum possible velocity penalty4A weight value at an elevation cost;
step four: obtaining standard deviation sigma of each item costiAnd average value
Figure FDA0003322207660000034
Calculating the coefficient of variation gamma of each costi：
Figure FDA0003322207660000031
And determining the weight value omega of each cost according to the ratio of the variation coefficients of the costsi(i ═ 1,2,3,4), the calculation formula is:
Figure FDA0003322207660000032
and the cost value of the impassable point is set as 1;
step five: and traversing all terrain points according to the steps to establish a visualized vehicle mobility distribution map, wherein the mobility of the vehicle on the terrain is reflected by using numerical values, and the numerical values are closer to 1, the lower the mobility of the vehicle is represented, the closer to 0, the higher the mobility of the vehicle is represented.
5. The method for planning a ground vehicle path based on mobility evaluation according to claim 1, wherein the step of planning a path by using the cost function of the improved a-Star algorithm comprises:
obtaining parameters of a cost function, including mobility cost, uphill times, accumulated uphill distance, path curvature and distance, wherein the formula of the cost function is as follows:
Figure FDA0003322207660000033
in the formula, CiAt a cost of mobility, NiFor accumulating the cost of ascending times, LiFor accumulating the cost of uphill distance, PiAs the cost of path curvature, ωa、ωb、ωc、ωdRespectively is the weight value of each cost;
the method is used for reducing the traversal number of the algorithm by presetting the high-mobility cost points and the non-passable points, and adjusting and optimizing according to the path planning result.
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