1 简介

研究机器人路径规划优化问题,机器人工作环境复杂,运动路径上存在许多障碍物.针对提高机器人安全导航性能问题,传统群智能算法存在早熟,搜索效率低等难题,难以获得全局最优路径.为了获得最优机器人运动路径,避免碰撞的发生,提出了一种人工蜂群算法的机器人路径规划方法.首先采用栅格法对机器人工作环境进行建模,然后机器人路径规划目标点作为蜜源,最后蜂群之间信息交换,协作搜索最优机器人运动路径.结果表明,人工蜂群算法解决了传统群智能算法存在的难题;加快了机器人路径规划求解速度,以较短时间找到最短机器人运动路径.

2 部分代码

%

function varargout = robotpath(varargin)

gui_Singleton = 1;

gui_State = struct('gui_Name',       mfilename, ...

                   'gui_Singleton',  gui_Singleton, ...

                   'gui_OpeningFcn', @robotpath_OpeningFcn, ...

                   'gui_OutputFcn',  @robotpath_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 fpp is made visible.

function robotpath_OpeningFcn(hObject, eventdata, handles, varargin)

handles.output = hObject;

% Update handles structure

guidata(hObject, handles);

% --- Outputs from this function are returned to the command line.

function varargout = robotpath_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;

%% Initialize map

function pushbutton1_Callback(hObject, eventdata, handles)

cla reset

% current_pos is a robot path including starting point, in which

% current_pos(:,1) represents the start position

current_pos= [-1;-1];

setappdata(0,'current_pos',current_pos);

% target is a robot goal position

target = [-1 ;-1];

setappdata(0,'target',target);

% map is a collection of obstacle in 2d 

% each row of the map defines an obstacle

% first column is a x position of obstacle

% second column is a y position of obstacle

% third column defines the length of the obstacle in x axis

% fourth column defines the length of the obstacle in y axis

map=[];

setappdata(0,'map',map);

axes(handles.axes2) % Select the proper axes

axis([-5,100,-5,100])

set(handles.axes2,'XMinorTick','on')

%% Insert obstacles

function pushbutton2_Callback(hObject, eventdata, handles)

%% Initialize Axes

axes(handles.axes2) % Select the proper axes

set(handles.axes2,'XMinorTick','on')

axis([1 100 1 100]);

    %%

    hold on

    h=msgbox('Draw a wall by using the left mouse button for start and right mouse button for ending the wall');

     uiwait(h,5);

     if ishandle(h)==1

         delete(h);

     end

     

    but=0;

    %but=1 left     but=3 right

    while((but~=1)&&(but~=3))

        [xs,ys,but]=ginput(1);

    end

%%

xs=round(xs);

ys=round(ys);

    if(xs <10)

        xs = xs-10;

    end

    if(ys < 10)

        ys = ys -10;

    end

width = 10;

height = 45;

map = getappdata(0,'map');

axes(handles.axes2) % Select the proper axes

%% Draw obstacle

    if(but == 1)

    rectangle('Position',[xs,ys,width,height],'FaceColor',[0 0 0])

    [m,n] = size(map);

    map(m+1,:) = [xs ys width height];

    setappdata(0,'map',map);

    else

     rectangle('Position',[xs,ys,height,width],'FaceColor',[0 0 0])  

     [m,n] = size(map);

    map(m+1,:) = [xs ys height width];

    setappdata(0,'map',map);

    end

    

set(handles.axes2,'XMinorTick','on')

map = getappdata(0,'map');

% Draw target

function pushbutton3_Callback(hObject, eventdata, handles)

but=0;

while(but~=1)

    [xval,yval,but]=ginput(1);

end

pos=[xval,yval];

setappdata(0,'target',pos);

axes(handles.axes2) 

hold on

post = [xval yval 4 4];

rectangle('Position',post,'FaceColor','r','Curvature',[1 1])

hold off

%% Start robot path finding procedure

function pushbutton4_Callback(hObject, eventdata, handles)

map = getappdata(0,'map');

target = getappdata(0,'target');

current_pos = getappdata(0,'current_pos');

if(target == [-1 -1])    

    msgbox('Please select the target position first');

    

elseif(current_pos(:,1) == [-1 ;-1])     

    

     msgbox('Please select the start position first');

else

    

    

    %% Find Coolision free path using Artificial Bee Colony Algorithm

     Vxy  = Create_Food_Points(map, target, 500,5,95 );

                hold on

        plot(Vxy(:,1),Vxy(:,2), 'go')  

        pause(1)

        refresh 

   abc_plot_handle = [];     

   for i = 1:50 

        [m n] = size(current_pos);

        [cost pos] = artificial_bee_colony(map, Vxy);            

        current_pos(:,n+1) = pos.Position';

        setappdata(0,'current_pos',current_pos);

         hold on

        

       abc_plot_handle(i) = plot(current_pos(1,:),current_pos(2,:),'--rs','LineWidth',2,...

                'MarkerEdgeColor','k',...

                'MarkerFaceColor','g',...

                'MarkerSize',10)

                    pause(2)

                    

        if ((cost < 5))

            [M N] =size(map)

            collide = 0;

               for i=1:M

   

                 collide = is_collide( map(i,:), current_pos(:,n+1), target');

                 if collide == 1

                     break;

                 end

               end

               if(collide == 0)

                 break;

               end

        end

   end

   

   

   [m n] = size(current_pos);

   post = [current_pos(n) current_pos(n) 4 4];

   hold on

   plot(current_pos(1,:),current_pos(2,:),'*')  

        

        %% Optimize path usin EP algorithm

        for i = 1:20

            

            current_pos = ep_algorithm( map, current_pos );

        end

        delete(abc_plot_handle);

                        plot(current_pos(1,:),current_pos(2,:),'--rs','LineWidth',2,...

                        'MarkerEdgeColor','k',...

                        'MarkerFaceColor','g',...

                        'MarkerSize',10)

                            pause(2)

        

        

          

end

% --- Executes on button press in pushbutton5.

function pushbutton5_Callback(hObject, eventdata, handles)

%% Draw starting point

function pushbutton9_Callback(hObject, eventdata, handles)

but=0;

while(but~=1)

    [xval,yval,but]=ginput(1);

end

current_pos=[xval;yval];

setappdata(0,'current_pos',current_pos);

axes(handles.axes2) 

hold on

post = [xval yval 4 4];

rectangle('Position',post,'FaceColor',[0 0.5 0.3],'Curvature',[1 1])

hold off

3 仿真结果

4 参考文献

[1]黎竹娟. "人工蜂群算法在移动机器人路径规划中的应用." 计算机仿真 29.12(2012):4.

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