First, we need to define the maze as a 2D matrix in MATLAB code. Here is an example:
Now we can implement the STAR algorithm to solve the maze. Here is an example implementation:
function solveMaze(mazeAxes)
% Set up maze
mazeSize = [10 10];
startX = 1;
startY = 2;
endX = 10;
endY = 9;
maze = [0 0 0 0 0 0 0 0 0 0;
0 1 0 1 1 0 0 1 1 0;
0 1 0 0 1 1 1 1 0 0;
0 1 1 0 0 0 0 0 0 0;
0 1 0 0 1 1 1 1 0 0;
0 1 1 0 0 0 0 1 1 0;
0 0 1 1 1 1 0 1 1 0;
0 1 0 0 0 1 0 1 1 0;
0 1 1 1 0 1 0 0 0 0;
0 0 0 0 0 0 0 0 0 0];
% Show initial maze
currPos = [startX startY];
drawMaze(maze, mazeAxes, currPos, [endX endY])
% Initialize data structures
openList = [startX startY 0];
cameFrom = zeros(mazeSize);
costSoFar = inf(mazeSize);
costSoFar(startX, startY) = 0;
% Run STAR algorithm
while ~isempty(openList)
% Get next node
currNode = openList(1,:);
openList(1,:) = [];
% Check if at goal
if currNode(1) == endX && currNode(2) == endY
% Reconstruct path
path = [endX endY];
while ~isequal(path(1,:), [startX startY])
newPath = cameFrom(path(1,1), path(1,2), :);
path = [squeeze(newPath) ; path];
end
% Show final path
drawMaze(maze, mazeAxes, [endX endY], [startX startY], path)
return
end
% Add neighbors to open list
for i = -1:1
for j = -1:1
if abs(i)+abs(j) == 1 && currNode(1)+i > 0 && currNode(1)+i <= mazeSize(1) && currNode(2)+j > 0 && currNode(2)+j <= mazeSize(2) && maze(currNode(1)+i, currNode(2)+j) == 0
newCost = costSoFar(currNode(1), currNode(2)) + 1; % unit cost
if newCost < costSoFar(currNode(1)+i, currNode(2)+j)
costSoFar(currNode(1)+i, currNode(2)+j) = newCost;
priority = newCost + heuristic([currNode(1)+i currNode(2)+j], [endX endY]);
cameFrom(currNode(1)+i, currNode(2)+j, :) = [currNode(1) currNode(2)];
openList = [openList ; currNode(1)+i currNode(2)+j priority];
end
end
end
end
% Sort open list by priority
[~, index] = sort(openList(:,3));
openList = openList(index,:);
% Show current position
currPos = currNode(1:2);
drawMaze(maze, mazeAxes, currPos, [endX endY])
end
error('Maze cannot be solved.');
end
function drawMaze(maze, mazeAxes, currPos, goalPos, path)
% Clear previous maze
cla(mazeAxes)
% Get maze size
[mazeRows, mazeCols] = size(maze);
% Draw maze
for row = 1:mazeRows
for col = 1:mazeCols
if maze(row,col) == 1
rectangle(mazeAxes, [col-1 row-1 1 1], 'FaceColor', 'black')
end
end
end
% Draw current position
if nargin > 2
rectangle(mazeAxes, [currPos(2)-1 currPos(1)-1 1 1], 'FaceColor', 'blue')
end
% Draw goal position
if nargin > 3
rectangle(mazeAxes, [goalPos(2)-1 goalPos(1)-1 1 1], 'FaceColor', 'green')
end
% Draw path
if nargin > 4
line(mazeAxes, path(:,2)-1, path(:,1)-1, 'Color', 'red')
end
% Set axis limits
xlim(mazeAxes, [0 mazeCols])
ylim(mazeAxes, [0 mazeRows])
end
function h = heuristic(pos1, pos2)
% Use Manhattan distance as heuristic
h = abs(pos1(1)-pos2(1)) + abs(pos1(2)-pos2(2));
end
To use this implementation in App Designer, you would need to create a UIAxes object in your app and pass it to the solveMaze function when you want to run the algorithm. You can also customize the maze by changing the maze matrix and the starting and ending positions in the solveMaze function.