DWA路径规划matlab算法代码

以下是一个MATLAB实现的DWA路径规划算法的简单示例代码：

classdef RobotModel
    % 机器人的动力学模型，这里简化为一个点质量模型，可以根据实际情况进行修改
    properties
        max_speed
        max_yaw_rate
    end
    
    methods
        function obj = RobotModel(max_speed, max_yaw_rate)
            obj.max_speed = max_speed;
            obj.max_yaw_rate = max_yaw_rate;
        end
        
        function state = simulate(obj, state, v, w, dt)
            x = state(1);
            y = state(2);
            yaw = state(3);
            x = x + v * cos(yaw) * dt;
            y = y + v * sin(yaw) * dt;
            yaw = yaw + w * dt;
            v = max(0, min(v, obj.max_speed));
            w = max(-obj.max_yaw_rate, min(w, obj.max_yaw_rate));
            state = [x; y; yaw; v; w];
        end
    end
end

classdef DWAPlanner
    % DWA路径规划算法
    properties
        robot_model
        max_speed
        max_yaw_rate
        max_accel
        max_dyaw_rate
        dt
        predict_time
        goal_tolerance
    end
    
    methods
        function obj = DWAPlanner(robot_model, max_speed, max_yaw_rate, max_accel, max_dyaw_rate, dt, predict_time, goal_tolerance)
            obj.robot_model = robot_model;
            obj.max_speed = max_speed;
            obj.max_yaw_rate = max_yaw_rate;
            obj.max_accel = max_accel;
            obj.max_dyaw_rate = max_dyaw_rate;
            obj.dt = dt;
            obj.predict_time = predict_time;
            obj.goal_tolerance = goal_tolerance;
        end
        
        function traj = plan(obj, state, goal)
            % 动态窗口的范围
            v_min = 0;
            v_max = obj.max_speed;
            w_min = -obj.max_yaw_rate;
            w_max = obj.max_yaw_rate;
            v_reso = 0.1;
            w_reso = 0.1;

            % 动态窗口评价
            best_traj = [];
            best_score = -inf;
            for v = v_min:v_reso:v_max
                for w = w_min:w_reso:w_max
                    traj = obj.generate_trajectory(state, v, w);
                    score = obj.evaluate_trajectory(traj, goal);
                    if score > best_score
                        best_traj = traj;
                        best_score = score;
                    end
                end
            end

            traj = best_traj;
        end
        
        % 生成一条轨迹，根据机器人动力学模型模拟运动
        function traj = generate_trajectory(obj, state, v, w)
            traj = state;
            for i = 1:round(obj.predict_time / obj.dt)
                state = obj.robot_model.simulate(state, v, w, obj.dt);
                traj = [traj, state];
            end
        end
        
        % 评价轨迹，根据预定义的代价函数进行评分
        function score = evaluate_trajectory(obj, traj, goal)
            dist = norm(traj(1:2, end) - goal(1:2));
            heading = abs(mod(traj(3, end) - goal(3), 2 * pi) - pi);
            speed = traj(4, end);
            score = exp(-dist / obj.goal_tolerance) + exp(-heading) + exp(-speed / obj.max_speed);
        end
    end
end

这只是一个简单的示例代码，实际上DWA路径规划算法的实现要考虑更多的细节和实际情况，需要在实际应用中进行修改和优化。