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mid360.yaml

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+/**:
+    ros__parameters:
+        feature_extract_enable: false
+        point_filter_num: 3
+        max_iteration: 4             # 增加迭代次数，提高精度
+        filter_size_surf: 0.15       # 减小滤波器尺寸，提高精度
+        filter_size_map: 0.15        # 减小地图滤波器尺寸，提高精度
+        cube_side_length: 2000.0
+        runtime_pos_log_enable: false
+        map_file_path: "./test.pcd"
+
+        common:
+            lid_topic:  "/livox/lidar"
+            imu_topic:  "/livox/imu"
+            time_sync_en: false        # 禁用时间同步以解决时间差问题
+            time_offset_lidar_to_imu: 0.0  # 重置时间偏移
+                                        # This param will take effect no matter what time_sync_en is. So if the time offset is not known exactly, please set as 0.0
+
+        preprocess:
+            lidar_type: 1                # 1 for Livox serials LiDAR, 2 for Velodyne LiDAR, 3 for ouster LiDAR, 4 for any other pointcloud input
+            scan_line:  4
+            blind: 0.1
+            timestamp_unit: 3
+            scan_rate: 5                 # 修复: 从20降到5以匹配实际雷达频率3.38Hz
+
+        mapping:
+            acc_cov: 0.1                 # 降低加速度计噪声协方差，减少漂移
+            gyr_cov: 0.1                 # 降低陀螺仪噪声协方差，减少漂移  
+            b_acc_cov: 0.001             # 降低加速度计bias噪声协方差
+            b_gyr_cov: 0.001             # 降低陀螺仪bias噪声协方差
+            fov_degree:    360.0
+            det_range:     100.0
+            extrinsic_est_en:  false      # true: enable the online estimation of IMU-LiDAR extrinsic
+            extrinsic_T: [ -0.011, -0.02329, 0.04412 ]
+            extrinsic_R: [ 1., 0., 0.,
+                            0., 1., 0.,
+                            0., 0., 1.]
+
+        publish:
+            path_en: true                # true: publish Path
+            effect_map_en: false         # true: publish Effects
+            map_en: true                 # true: publish Map cloud
+            scan_publish_en:  true       # false: close all the point cloud output
+            dense_publish_en: false      # false: low down the points number in a global-frame point clouds scan.
+            scan_bodyframe_pub_en: true  # true: output the point cloud scans in IMU-body-frame
+
+        pcd_save:
+            pcd_save_en: true
+            interval: -1                 # how many LiDAR frames saved in each pcd file; 
+                                        # -1 : all frames will be saved in ONE pcd file, may lead to memory crash when having too much frames.