rrt matlab算法,rrt算法matlab代码

以下是基于 RRT（Rapidly-exploring Random Tree）算法的 Matlab 代码，用于构建机器人路径规划：

clear all; close all; clc

% Environment and robot parameters
xMin = 0;
xMax = 10;
yMin = 0;
yMax = 10;
obs = [4 4 1; 6 6 1];

robotLength = 0.5;
robotWidth = 0.5;

% Start and goal positions
startPos = [1,1];
goalPos = [9,9];

% RRT parameters
maxNodes = 5000;
stepSize = 0.5;

nodes(1).x = startPos(1);
nodes(1).y = startPos(2);
nodes(1).parent = 0;

for i = 2:maxNodes
    x = rand*(xMax-xMin) + xMin;
    y = rand*(yMax-yMin) + yMin;
    node = [x,y];
    
    % Check if node is inside an obstacle
    insideObs = 0;
    for j = 1:size(obs,1)
        if sqrt((node(1)-obs(j,1))^2 + (node(2)-obs(j,2))^2) < obs(j,3)
            insideObs = 1;
            break;
        end
    end
    
    if insideObs == 1
        continue;
    end
    
    % Find the nearest node
    dist = inf;
    nearestNode = 0;
    for j = 1:length(nodes)
        d = sqrt((node(1)-nodes(j).x)^2 + (node(2)-nodes(j).y)^2);
        if d < dist
            dist = d;
            nearestNode = j;
        end
    end
    
    % Check if there is a direct path between the nearest node and the new node
    theta = atan2(node(2)-nodes(nearestNode).y, node(1)-nodes(nearestNode).x);
    xTest = nodes(nearestNode).x + stepSize*cos(theta);
    yTest = nodes(nearestNode).y + stepSize*sin(theta);
    if sqrt((xTest-node(1))^2 + (yTest-node(2))^2) > stepSize
        continue;
    end
    
    % Check if the direct path is inside an obstacle
    insideObs = 0;
    for j = 1:size(obs,1)
        if sqrt((xTest-obs(j,1))^2 + (yTest-obs(j,2))^2) < obs(j,3)
            insideObs = 1;
            break;
        end
    end
    
    if insideObs == 1
        continue;
    end
    
    % Add the new node to the tree
    nodes(end+1).x = xTest;
    nodes(end).y = yTest;
    nodes(end).parent = nearestNode;
    
    % Check if the goal has been reached
    if sqrt((nodes(end).x-goalPos(1))^2 + (nodes(end).y-goalPos(2))^2) < stepSize
        break;
    end
end

% Plot the obstacles
figure(1)
hold on
axis([xMin xMax yMin yMax])
for i = 1:size(obs,1)
    rectangle('Position',[obs(i,1)-obs(i,3), obs(i,2)-obs(i,3), 2*obs(i,3), 2*obs(i,3)], 'Curvature', [1,1], 'FaceColor', 'r')
end

% Plot the tree
for i = 2:length(nodes)
    x = [nodes(i).x, nodes(nodes(i).parent).x];
    y = [nodes(i).y, nodes(nodes(i).parent).y];
    plot(x,y,'k')
end

% Find the path from start to goal
path = [nodes(end).x, nodes(end).y];
while nodes(end).parent ~= 0
    endNode = nodes(end);
    path = [endNode.x, endNode.y; path];
    endNode = nodes(endNode.parent);
end
path = [startPos; path];

% Plot the path
plot(path(:,1), path(:,2), 'b', 'LineWidth', 2)

这段代码会生成一个基于 RRT 算法的路径规划过程，其中包括环境参数、机器人参数、起始位置、目标位置和 RRT 参数。代码将生成一个随机树，以搜索从起始位置到目标位置的路径。最终，该代码会绘制出路径和环境。