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【路径规划】基于A星算法之求解最短路径matlab GUI

2021-08-18 08:49 作者:Matlab工程师  | 我要投稿

一、简介

A算法
A算法是一种典型的启发式搜索算法,建立在Dijkstra算法的基础之上,广泛应用于游戏地图、现实世界中,用来寻找两点之间的最短路径。A算法最主要的是维护了一个启发式估价函数,如式(1)所示。
f(n)=g(n)+h(n)(1)
其中,f(n)是算法在搜索到每个节点时,其对应的启发函数。它由两部分组成,第一部分g(n)是起始节点到当前节点实际的通行代价,第二部分h(n)是当前节点到终点的通行代价的估计值。算法每次在扩展时,都选取f(n)值最小的那个节点作为最优路径上的下一个节点。
在实际应用中,若以最短路程为优化目标,h(n)常取作当前点到终点的欧几里得距离(Euclidean Distance)或曼哈顿距离(Manhattan Distance)等。若令h(n)=0,表示没有利用任何当前节点与终点的信息,A算法就退化为非启发的Dijkstra算法,算法搜索空间随之变大,搜索时间变长。
A*算法步骤如下,算法维护两个集合:P表与Q表。P表存放那些已经搜索到、但还没加入最优路径树上的节点;Q表维护那些已加入最优路径树上的节点。
(1)P表、Q表置空,将起点S加入P表,其g值置0,父节点为空,路网中其他节点g值置为无穷大。
(2)若P表为空,则算法失败。否则选取P表中f值最小的那个节点,记为BT,将其加入Q表中。判断BT是否为终点T,若是,转到步骤(3);否则根据路网拓扑属性和交通规则找到BT的每个邻接节点NT,进行下列步骤:

①计算NT的启发值
f(NT)=g(NT)+h(NT)(2)
g(NT)=g(BT)+cost(BT, NT)(3)
其中,cost(BT, NT)是BT到NT的通行代价。
②如果NT在P表中,且通过式(3)计算的g值比NT原先的g值小,则将NT的g值更新为式(3)结果,并将NT的父节点设为BT。
③如果NT在Q表中,且通过式(3)计算的g值比NT原先的g值小,则将NT的g值更新为式(3)结果,将NT的父节点设为BT,并将NT移出到P表中。
④若NT既不在P表,也不在Q表中,则将NT的父节点设为BT,并将NT移到P表中。
⑤转到步骤(2)继续执行。
(3)从终点T回溯,依次找到父节点,并加入优化路径中,直到起点S,即可得出优化路径。

二、源代码

function varargout = A_GUI(varargin) % A_GUI MATLAB code for A_GUI.fig %      A_GUI, by itself, creates a new A_GUI or raises the existing %      singleton*. % %      H = A_GUI returns the handle to a new A_GUI or the handle to %      the existing singleton*. % %      A_GUI('CALLBACK',hObject,eventData,handles,...) calls the local %      function named CALLBACK in A_GUI.M with the given input arguments. % %      A_GUI('Property','Value',...) creates a new A_GUI or raises the %      existing singleton*.  Starting from the left, property value pairs are %      applied to the GUI before A_GUI_OpeningFcn gets called.  An %      unrecognized property name or invalid value makes property application %      stop.  All inputs are passed to A_GUI_OpeningFcn via varargin. % %      *See GUI Options on GUIDE's Tools menu.  Choose "GUI allows only one %      instance to run (singleton)". % % See also: GUIDE, GUIDATA, GUIHANDLES % Edit the above text to modify the response to help A_GUI % Last Modified by GUIDE v2.5 21-Oct-2018 17:10:48 % Begin initialization code - DO NOT EDIT gui_Singleton = 1; gui_State = struct('gui_Name',       mfilename, ...                   'gui_Singleton',  gui_Singleton, ...                   'gui_OpeningFcn', @A_GUI_OpeningFcn, ...                   'gui_OutputFcn',  @A_GUI_OutputFcn, ...                   'gui_LayoutFcn',  [] , ...                   'gui_Callback',   []); if nargin && ischar(varargin{1})    gui_State.gui_Callback = str2func(varargin{1}); end if nargout    [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); else    gui_mainfcn(gui_State, varargin{:}); end % End initialization code - DO NOT EDIT % --- Executes just before A_GUI is made visible. function A_GUI_OpeningFcn(hObject, eventdata, handles, varargin) % This function has no output args, see OutputFcn. % hObject    handle to figure % eventdata  reserved - to be defined in a future version of MATLAB % handles    structure with handles and user data (see GUIDATA) % varargin   command line arguments to A_GUI (see VARARGIN) % Choose default command line output for A_GUI handles.output = hObject; % Update handles structure guidata(hObject, handles); % UIWAIT makes A_GUI wait for user response (see UIRESUME) % uiwait(handles.figure1); % --- Outputs from this function are returned to the command line. function varargout = A_GUI_OutputFcn(hObject, eventdata, handles) % varargout  cell array for returning output args (see VARARGOUT); % hObject    handle to figure % eventdata  reserved - to be defined in a future version of MATLAB % handles    structure with handles and user data (see GUIDATA) % Get default command line output from handles structure varargout{1} = handles.output; % --- Executes on button press in pushbutton1. function pushbutton1_Callback(hObject, eventdata, handles) % hObject    handle to pushbutton1 (see GCBO) % eventdata  reserved - to be defined in a future version of MATLAB % handles    structure with handles and user data (see GUIDATA) % set up color map for display 生成彩色地图 global cmap; global map; global n_r; global n_c; global state; cmap = [1 1 1; ...% 1 -白色-无障碍        0 0 0; ...% 2 -黑色-有障碍        0 0.8 0; ...% 3 -绿色-已搜索        0 0.4 0; ...% 4 -粉色-正在搜索        0 1 1; ...% 5 -浅蓝色-起始点        1 1 0; ...% 6 -黄色-目标点        0 0 1];   % 7 -蓝色-最终路径 colormap(cmap); %生成随机地图 map = zeros(n_r,n_c); randmap = rand(n_r,n_c); for i = 2:(sub2ind(size(randmap),n_r,n_c)-1)    if (randmap(i) >= 0.75)        map(i) = 2;    end end map(1, 1) = 5; % start_coords 起点坐标 map(n_r, n_c) = 6; % dest_coords 终点坐标 image(1.5,1.5,map); grid on; axis image; set(handles.text5,'string','随机地图生成完毕'); % --- Executes on button press in pushbutton2. function pushbutton2_Callback(hObject, eventdata, handles) % hObject    handle to pushbutton2 (see GCBO) % eventdata  reserved - to be defined in a future version of MATLAB % handles    structure with handles and user data (see GUIDATA) %搜索最佳路径 global n_r; global n_c; global cmap; global map; global state; nrows = n_r; ncols = n_c; start_node = sub2ind(size(map), 1, 1); %sub2ind()函数将矩阵中的某个元素的线性序号计算出来 %线性索引号例子:2*2矩阵[1 3;中,1是第一个,5是第二个 %                       5 7]  ,3是第三个,7是第四个 %(matlab是列优先,不是我们通常习惯的行优先) dest_node = sub2ind(size(map), n_r, n_c); % Initialize distance array 初始化距离数组 distanceFromStart = Inf(nrows,ncols); distanceFromStart(start_node) = 0 ; [X, Y] = meshgrid (1:ncols, 1:nrows); H = abs(Y - n_r) + abs(X - n_c); f = Inf(nrows,ncols); f(start_node) = H(start_node); % For each grid cell this array holds the index of its parent 对于每个网格单元,该数组都保存其父单元的索引 parent = zeros(nrows,ncols); % Main Loop while true  % Draw current map  map(start_node) = 5;  map(dest_node) = 6;  image(1.5, 1.5, map);  grid on; %网格  axis image; %显示坐标  drawnow; %刷新屏幕  % Find the node with the minimum distance 找到距离最短的节点 %   [min_dist, current] = min(distanceFromStart(:)); [~, current] = min(f(:)); [min_dist, ~] = min(distanceFromStart(:));  if ((current == dest_node) || isinf(min_dist)) %TF = isinf(A)  返回一个和A尺寸一样的数组, 如果A中某个元素是inf  (无穷), 则对应TF中元素是1, 否则TF中对应元素是0。       break;  end;  %搜索中心的索引坐标:current,  %搜索中心与起始点的路程:min_dist  % 这两个值后面会用。  map(current) = 3; %   distanceFromStart(current) = Inf; f(current) = Inf;  [i, j] = ind2sub(size(distanceFromStart), current); %索引号变为坐标  neighbor = [i-1,j;              i+1,j;              i,j+1;              i,j-1];    outRangetest = (neighbor(:,1)<1) + (neighbor(:,1)>nrows)+(neighbor(:,2)<1) + (neighbor(:,2)>ncols);    locate = find(outRangetest>0);  %返回outRangetest中大于0的元素的相对应的线性索引值。    neighbor(locate,:)=[];    neighborIndex = sub2ind(size(map),neighbor(:,1),neighbor(:,2)); for i=1:length(neighborIndex) if (map(neighborIndex(i))~=2) && (map(neighborIndex(i))~=3 && map(neighborIndex(i))~= 5)     map(neighborIndex(i)) = 4;   if (distanceFromStart(neighborIndex(i))>= min_dist + 1 )           distanceFromStart(neighborIndex(i)) = min_dist+1;         parent(neighborIndex(i)) = current;           f(neighborIndex(i)) = H(neighborIndex(i));        % pause(0.02);   end  end end end % %% if (isinf(distanceFromStart(dest_node)))     %route = [];     disp('路径搜索失败');     set(handles.text5,'string','路径搜索失败'); else     %提取路线坐标     set(handles.text5,'string','路径搜索成功');     route = [dest_node];       while (parent(route(1)) ~= 0)               route(1);               parent(route(1))               route = [parent(route(1)), route] ;        end

三、运行结果

在这里插入图片描述



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