update readme for kitti

README.md

@@ -113,6 +113,9 @@ The user needs to prepare the point cloud data in the correct format for cloud d
   * Ouster (OS1-128) dataset. No extrinsics need to be changed for this dataset if you are using the default settings. Please follow the Ouster notes below to configure the package to run with Ouster data. A video of the dataset can be found on [YouTube](https://youtu.be/O7fKgZQzkEo):
     - [**Rooftop dataset**](https://drive.google.com/file/d/1Qy2rZdPudFhDbATPpblioBb8fRtjDGQj/view?usp=sharing)
 
+  * KITTI dataset. The extrinsics can be found in the Notes KITTI section below. To generate more bags using other KITTI raw data, you can use the python script provided in "config/doc/kitti2bag".
+    - [**2011_09_30_drive_0028**](https://drive.google.com/file/d/12h3ooRAZVTjoMrf3uv1_KriEXm33kHc7/view?usp=sharing)
+
 ## Run the package
 
 1. Run the launch file:
@@ -139,7 +142,18 @@ rosbag play your-bag.bag -r 3
     <img src="./config/doc/gps-demo.gif" alt="drawing" width="400"/>
 </p>
 
-  - **KITTI dataset:** Testing with the KITTI dataset with LIO-SAM can be problematic. LIO-SAM needs a very good IMU source to function properly. The KITTI odometry sequence gives no IMU data. The KITTI raw synced dataset only gives IMU data at 10Hz, which is impossible to perform IMU pre-integration during a lidar scan. Though the KITTI raw unsynced dataset gives IMU data at 100Hz, the timestamps of the data is inconsistent, which causes pre-integration failure. Testing LIO-SAM with KITTI dataset is very similar to testing VINS-Mono with it. Interested users can find more discussions about this problem can be found [here](https://github.com/HKUST-Aerial-Robotics/VINS-Mono/issues/222).
+  - **KITTI:** Since LIO-SAM needs a high-frequency IMU for function properly, we need to use KITTI raw data for testing. One problem remains unsolved is that the intrinsics of the IMU is unknown, which has a big impact on the accuracy of LIO-SAM. Download the provided sample data and make the following changes in "params.yaml":
+    - extrinsicTrans: [-8.086759e-01, 3.195559e-01, -7.997231e-01] 
+    - extrinsicRot: [9.999976e-01, 7.553071e-04, -2.035826e-03, -7.854027e-04, 9.998898e-01, -1.482298e-02, 2.024406e-03, 1.482454e-02, 9.998881e-01]
+    - extrinsicRPY: [9.999976e-01, 7.553071e-04, -2.035826e-03, -7.854027e-04, 9.998898e-01, -1.482298e-02, 2.024406e-03, 1.482454e-02, 9.998881e-01]
+    - N_SCAN: 64
+    - downsampleRate: 2 or 4
+    - loopClosureEnableFlag: true or false
+
+<p align='center'>
+    <img src="./config/doc/kitti-map.png" alt="drawing" width="300"/>
+    <img src="./config/doc/kitti-demo.gif" alt="drawing" width="300"/>
+</p>
 
   - **Ouster lidar:** To make LIO-SAM work with Ouster lidar, some preparations needs to be done on hardware and software level.
     - Hardware:

config/params.yaml

@@ -20,7 +20,7 @@ lio_sam:
   N_SCAN: 16                                  # number of lidar channel (i.e., 16, 32, 64, 128)
   Horizon_SCAN: 1800                          # lidar horizontal resolution (Velodyne:1800, Ouster:512,1024,2048)
   timeField: "time"                           # point timestamp field, Velodyne - "time", Ouster - "t"
-  downsampleRate: 4                           # default: 1. Downsample your data if too many points. i.e., 16 = 64 / 4, 16 = 16 / 1 
+  downsampleRate: 1                           # default: 1. Downsample your data if too many points. i.e., 16 = 64 / 4, 16 = 16 / 1 
 
   # IMU Settings
   imuAccNoise: 3.9939570888238808e-03
@@ -70,7 +70,7 @@ lio_sam:
   surroundingKeyframeSearchRadius: 50.0         # meters, within n meters scan-to-map optimization (when loop closure disabled)
 
   # Loop closure
-  loopClosureEnableFlag: false
+  loopClosureEnableFlag: true
   surroundingKeyframeSize: 25                   # submap size (when loop closure enabled)
   historyKeyframeSearchRadius: 15.0             # meters, key frame that is within n meters from current pose will be considerd for loop closure
   historyKeyframeSearchTimeDiff: 30.0           # seconds, key frame that is n seconds older will be considered for loop closure

launch/include/config/rviz.rviz

@@ -163,7 +163,7 @@ Visualization Manager:
           Topic: /lio_sam/mapping/odometry
           Unreliable: false
           Value: false
-      Enabled: true
+      Enabled: false
       Name: Odometry
     - Class: rviz/Group
       Displays:
@@ -179,10 +179,10 @@ Visualization Manager:
           Color: 255; 255; 255
           Color Transformer: Intensity
           Decay Time: 0
-          Enabled: false
+          Enabled: true
           Invert Rainbow: false
           Max Color: 255; 255; 255
-          Max Intensity: 0.99000001
+          Max Intensity: 0.959999979
           Min Color: 0; 0; 0
           Min Intensity: 0
           Name: Velodyne
@@ -196,7 +196,7 @@ Visualization Manager:
           Unreliable: false
           Use Fixed Frame: true
           Use rainbow: true
-          Value: false
+          Value: true
         - Alpha: 1
           Autocompute Intensity Bounds: true
           Autocompute Value Bounds:
@@ -209,10 +209,10 @@ Visualization Manager:
           Color: 255; 255; 255
           Color Transformer: Intensity
           Decay Time: 0
-          Enabled: true
+          Enabled: false
           Invert Rainbow: false
           Max Color: 255; 255; 255
-          Max Intensity: 0.99000001
+          Max Intensity: 0.790000021
           Min Color: 0; 0; 0
           Min Intensity: 0
           Name: Reg Cloud
@@ -226,7 +226,7 @@ Visualization Manager:
           Unreliable: false
           Use Fixed Frame: true
           Use rainbow: true
-          Value: true
+          Value: false
       Enabled: true
       Name: Point Cloud
     - Class: rviz/Group

src/mapOptmization.cpp

@@ -443,7 +443,7 @@ class mapOptimization : public ParamServer
         if (loopClosureEnableFlag == false)
             return;
 
-        ros::Rate rate(1);
+        ros::Rate rate(0.5);
         while (ros::ok())
         {
             rate.sleep();