A星算法不过障碍物顶点matlab代码

A星算法是一种用于计算最短路径的启发式搜索算法。下面是一个简单的Matlab代码示例，用于实现A星算法来避开障碍物顶点：

function [path] = AStarAlgorithm(start, goal, obstacles)
    openSet = start;
    closedSet = [];
    gScore = inf(size(obstacles));
    gScore(start) = 0;
    fScore = inf(size(obstacles));
    fScore(start) = heuristic(start, goal);
    
    while ~isempty(openSet)
        current = getLowestFScore(openSet, fScore);
        if current == goal
            path = reconstructPath(current);
            return
        end
        
        openSet = removeElement(openSet, current);
        closedSet = [closedSet; current];
        
        neighbors = getNeighbors(current, obstacles);
        for i = 1:length(neighbors)
            neighbor = neighbors(i);
            if ismember(neighbor, closedSet)
                continue
            end
            
            tentativeGScore = gScore(current) + distance(current, neighbor);
            if ~ismember(neighbor, openSet)
                openSet = [openSet; neighbor];
            elseif tentativeGScore >= gScore(neighbor)
                continue
            end
            
            gScore(neighbor) = tentativeGScore;
            fScore(neighbor) = gScore(neighbor) + heuristic(neighbor, goal);
        end
    end
    path = [];
end

function [element] = getLowestFScore(set, fScore)
    [~, index] = min(fScore(set));
    element = set(index);
end

function [set] = removeElement(set, element)
    set(set == element) = [];
end

function [neighbors] = getNeighbors(current, obstacles)
    % 在这里实现获取邻居顶点的逻辑
end

function [h] = heuristic(current, goal)
    % 在这里实现启发式函数的逻辑
end

function [d] = distance(start, goal)
    % 在这里实现计算两个顶点之间距离的逻辑
end

请注意，该代码示例中的getNeighbors、heuristic和distance函数需要根据实际情况进行实现，以便正确计算邻居顶点、启发式函数和顶点之间的距离。这些函数的实现将取决于您的具体问题和数据结构。