【无人机三维路径规划】基于树木生长算法TGA实现复杂城市地形下无人机避障三维航迹规划附Matlab代码

% 定义无人机起始位置和目标位置
start_point = [0, 0, 0]; % 起始位置 [x, y, z]
target_point = [100, 100, 100]; % 目标位置 [x, y, z]

% 定义城市地形和障碍物信息
city_map = imread(‘city_map.png’); % 城市地形图像
obstacles = [
20, 30, 10; % 障碍物1位置 [x, y, z]
50, 60, 20; % 障碍物2位置 [x, y, z]
80, 90, 15; % 障碍物3位置 [x, y, z]
];

% 定义TGA参数
num_trees = 50; % 树木数量
max_iterations = 100; % 最大迭代次数
step_size = 1; % 步长

% 定义适应度函数
fitness_func = @(x) objective_func(x, start_point, target_point, city_map, obstacles);

% 初始化树木
trees = unifrnd(0, 1, num_trees, 3); % 初始位置随机分布
best_solution = [];
best_fitness = Inf;

% 迭代优化
for iteration = 1:max_iterations
% 计算适应度值
fitness_values = fitness_func(trees);

% 更新最优解
[min_fitness, min_index] = min(fitness_values);
if min_fitness < best_fitnessbest_solution = trees(min_index, :);best_fitness = min_fitness;
end% 生长新树
new_trees = zeros(num_trees, 3);
for i = 1:num_trees% 选择父树parent_index = select_parent(fitness_values);% 生长新树new_trees(i, :) = trees(parent_index, :) + step_size * randn(1, 3);% 限制位置范围new_trees(i, :) = max(new_trees(i, :), 0);new_trees(i, :) = min(new_trees(i, :), 100);
end% 更新树木
trees = new_trees;% 显示当前迭代结果
disp(['Iteration: ', num2str(iteration), '  Best Fitness: ', num2str(best_fitness)]);

end

% 显示最优解
disp(‘Optimization finished.’);
disp(['Best Fitness: ', num2str(best_fitness)]);
disp(‘Best Solution:’);
disp(best_solution);

% 可视化航迹规划结果
visualize_solution(start_point, target_point, city_map, obstacles, best_solution);