1

src/FAST_LIO_LOCALIZATION/PCD/M4.yaml

@@ -0,0 +1,7 @@
+image: /home/robofish/jyc/mid360/src/FAST_LIO_LOCALIZATION/PCD/M4.pgm
+resolution: 0.050000
+origin: [-22.123611, -17.241680, 0.000000]
+negate: 0
+occupied_thresh: 0.65
+free_thresh: 0.196
+

src/FAST_LIO_LOCALIZATION/launch/localization_MID360.launch

@@ -37,7 +37,11 @@
 
 	<!-- load 2d map -->
 	<arg name="2dmap" default="M4.yaml" />
+<<<<<<< HEAD
 	<node name = "map_server" pkg = "map_server" type = "map_server" args="$(find fast_lio_localization)/PCD/m4.yaml /map:=prior_map"/>
+=======
+	<node name = "map_server" pkg = "map_server" type = "map_server" args="$(find fast_lio_localization)/PCD/M4.yaml /map:=prior_map"/>
+>>>>>>> 710b3fc3ab857cb452f1e5c38d1599436191b8de
 
 	<!-- pointscloud2 to laserscans -->
 	<include file="$(find fast_lio_localization)/launch/PointsCloud2toLaserscan.launch">

src/FAST_LIO_LOCALIZATION/scripts/global_localization.py

@@ -216,7 +216,7 @@ if __name__ == '__main__':
 
     # The threshold of global localization,
     # only those scan2map-matching with higher fitness than LOCALIZATION_TH will be taken
-    LOCALIZATION_TH = 0.95
+    LOCALIZATION_TH = 0.8
 
     # FOV(rad), modify this according to your LiDAR type
     FOV = 6.28

src/pcd2pgm/launch/run.launch

@@ -2,7 +2,7 @@
 <launch>
 <node pkg="pcd2pgm" name="pcd2pgm" type="pcd2pgm" output="screen">
 <!-- 存放pcd文件的路径-->
-<param name="file_directory" value= "/home/cmrt/mid360/ws_livox/src/FAST_LIO/PCD/" />
+<param name="file_directory" value= "/home/robofish/jyc/mid360/src/FAST_LIO/PCD/" />
 <!-- pcd文件名称-->
 <param name="file_name" value= "scans" />
 <!-- 选取的范围　最小的高度-->