本文主要是介绍【路径规划】基于matlab GUI改进的遗传算法机器人栅格地图最短路径规划【含Matlab 703期】，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！
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路径规划（Matlab）
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⛄一、遗传算法简介
1 引言
2 遗传算法理论
2.1 遗传算法的生物学基础
2.2 遗传算法的理论基础
2.3 遗传算法的基本概念
2.4 标准的遗传算法
2.5 遗传算法的特点
2.6 遗传算法的改进方向
3 遗传算法流程
4 关键参数说明
⛄二、部分源代码
function varargout = newGUI(varargin)
% NEWGUI MATLAB code for newGUI.fig
% NEWGUI, by itself, creates a new NEWGUI or raises the existing
% singleton*.
%
% H = NEWGUI returns the handle to a new NEWGUI or the handle to
% the existing singleton*.
%
% NEWGUI(‘CALLBACK’,hObject,eventData,handles,…) calls the local
% function named CALLBACK in NEWGUI.M with the given input arguments.
%
% NEWGUI(‘Property’,‘Value’,…) creates a new NEWGUI or raises the
% existing singleton*. Starting from the left, property value pairs are
% applied to the GUI before newGUI_OpeningFcn gets called. An
% unrecognized property name or invalid value makes property application
% stop. All inputs are passed to newGUI_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 newGUI
% Last Modified by GUIDE v2.5 02-Feb-2020 22:22:09
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct(‘gui_Name’, mfilename, …
‘gui_Singleton’, gui_Singleton, …
‘gui_OpeningFcn’, @newGUI_OpeningFcn, …
‘gui_OutputFcn’, @newGUI_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 newGUI is made visible.
function newGUI_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 newGUI (see VARARGIN)
% Choose default command line output for newGUI
handles.output = hObject;
% Update handles structure
guidata(hObject, handles);
% UIWAIT makes newGUI wait for user response (see UIRESUME)
% uiwait(handles.figure1);
% — Outputs from this function are returned to the command line.
function varargout = newGUI_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;
function edit1_Callback(hObject, eventdata, handles)
% hObject handle to edit1 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,‘String’) returns contents of edit1 as text
% str2double(get(hObject,‘String’)) returns contents of edit1 as a double
% — Executes during object creation, after setting all properties.
function edit1_CreateFcn(hObject, eventdata, handles)
% hObject handle to edit1 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,‘BackgroundColor’), get(0,‘defaultUicontrolBackgroundColor’))
set(hObject,‘BackgroundColor’,‘white’);
end
function edit2_Callback(hObject, eventdata, handles)
% hObject handle to edit2 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,‘String’) returns contents of edit2 as text
% str2double(get(hObject,‘String’)) returns contents of edit2 as a double
% — Executes during object creation, after setting all properties.
function edit2_CreateFcn(hObject, eventdata, handles)
% hObject handle to edit2 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,‘BackgroundColor’), get(0,‘defaultUicontrolBackgroundColor’))
set(hObject,‘BackgroundColor’,‘white’);
end
function edit3_Callback(hObject, eventdata, handles)
% hObject handle to edit3 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: get(hObject,‘String’) returns contents of edit3 as text
% str2double(get(hObject,‘String’)) returns contents of edit3 as a double
% — Executes during object creation, after setting all properties.
function edit3_CreateFcn(hObject, eventdata, handles)
% hObject handle to edit3 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called
% Hint: edit controls usually have a white background on Windows.
% See ISPC and COMPUTER.
if ispc && isequal(get(hObject,‘BackgroundColor’), get(0,‘defaultUicontrolBackgroundColor’))
set(hObject,‘BackgroundColor’,‘white’);
end
% — Executes on button press in pushbutton1.
function pushbutton1_Callback(hObject, eventdata, handles)
global G;
global X_min_path;
global Y_min_path;
global Min_path_value;
global Mean_path_value;
global colorbar1;
NP=get(handles.edit4,‘String’);% 种群数量
max_gen=get(handles.edit3,‘String’);
a=get(handles.edit1,‘String’);
b=get(handles.edit2,‘String’);
NP=str2double(NP);
a=str2double(a);
b=str2double(b);
max_gen=str2double(max_gen);
% disp([NP,a,b])
% disp(G)
p_start = 0; % 起始序号
p_end = size(G,1)*size(G,2)-1; % 终止序号
%NP = 200; % 种群数量
%max_gen = 50; % 最大进化代数
pc = 0.8; % 交叉概率
pm = 0.2; % 变异概率
%init_path = [];
z = 1;
new_pop1 = {}; % 元包类型路径
[y, x] = size(G);
% 起点所在列（从左到右编号1.2.3…）
xs = mod(p_start, x) + 1;
% 起点所在行（从上到下编号行1.2.3…）
ys = fix(p_start / x) + 1;
% 终点所在列、行
xe = mod(p_end, x) + 1;
ye = fix(p_end / x) + 1;
% 种群初始化step1，必经节点,从起始点所在行开始往上，在每行中挑选一个自由栅格，构成必经节点
pass_num = ye - ys + 1;
% disp(pass_num)
% disp(NP);
pop = zeros(NP, pass_num);
for i = 1 : NP
pop(i, 1) = p_start;
j = 1;
% 除去起点和终点
for yk = ys+1 : ye-1
j = j + 1;
% 每一行的可行点
can = [];
for xk = 1 : x
% 栅格序号
no = (xk - 1) + (yk - 1) * x;
if G(yk, xk) == 0
% 把点加入can矩阵中
can = [can no];
end
end
can_num = length(can);
% 产生随机整数
index = randi(can_num);
% 为每一行加一个可行点
pop(i, j) = can(index);
end
⛄三、运行结果
⛄四、matlab版本及参考文献
1 matlab版本
2014a
2 参考文献
[1]赵杰,王馨阳,王贺.改进遗传算法的救援机器人路径规划[J].黑龙江科技大学学报. 2022,32(03)
3 备注
简介此部分摘自互联网，仅供参考，若侵权，联系删除
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