init tuning localization page

Signed-off-by: ismetatabay <ismet@leodrive.ai>

docs/how-to-guides/integrating-autoware/tuning-parameters-and-performance/tuning-parameters/index.md

@@ -36,7 +36,7 @@ general information about the YTU Davutpaşa Campus:
 <figure markdown>
   ![ytu-campus-environment](images/ytu-campus.png){ align=center }
   <figcaption>
-    Yıldız Technical University (YTU) campus map. 
+    Yıldız Technical University (YTU) campus map.
   </figcaption>
 </figure>
 
@@ -54,7 +54,7 @@ we have converted the output map into MGRS format.
 <figure markdown>
   ![ytu-campus-pcd-map](images/ytu-campus-pcd-map.png){ align=center }
   <figcaption>
-    Yıldız Technical University (YTU) campus pointcloud map. 
+    Yıldız Technical University (YTU) campus pointcloud map.
   </figcaption>
 </figure>
 
@@ -67,6 +67,6 @@ information on the Lanelet2 map creation process, please refer to the [`Creating
 <figure markdown>
   ![ytu-campus-lanelet2-map](images/ytu-campus-lanelet2-map.png){ align=center }
   <figcaption>
-    Yıldız Technical University (YTU) campus lanelet2 map. 
+    Yıldız Technical University (YTU) campus lanelet2 map.
   </figcaption>
 </figure>

docs/how-to-guides/integrating-autoware/tuning-parameters-and-performance/tuning-parameters/localization-tuning/index.md

@@ -1,3 +1,144 @@
 # Tuning localization
 
 ## Introduction
+
+In this section,
+our focus will be on refining localization accuracy within the YTU Campus environment through updates to localization parameters and methods.
+Our approach entails using NDT as the pose input source,
+and the Gyro Odometer as the twist input source.
+These adjustments play a pivotal role
+in achieving a heightened level of precision and reliability in our localization processes,
+ensuring optimal performance in the specific conditions of the YTU campus.
+
+## NDT parameter tuning
+
+### Crop-box filter for localization input
+
+- In our campus environment, certain areas can be challenging for NDT localization,
+  particularly those near cliffs or wooded areas that are far from buildings.
+
+<figure markdown>
+  ![ytu-campus-pcd-range](images/pcd-range-cloud-compare.png){ align=center }
+  <figcaption>
+    Yıldız Technical University (YTU) campus challenging areas for NDT localization.
+  </figcaption>
+</figure>
+
+- In these areas,
+  the default NDT range
+  (which involves cropping the NDT input point cloud at the localization utility point cloud pipeline)
+  may prove insufficient for aligning point clouds.
+  The default NDT input point cloud parameters are shown below:
+
+!!! note " The default [crop_box_filter_measurement_range.param.yaml](https://github.com/autowarefoundation/autoware_launch/blob/main/autoware_launch/config/localization/crop_box_filter_measurement_range.param.yaml) file for localization util."
+
+    ```yaml
+    /**:
+      ros__parameters:
+      input_frame: "base_link"
+      output_frame: "base_link"
+      min_x: -60.0
+      max_x: 60.0
+      min_y: -60.0
+      max_y: 60.0
+      min_z: -30.0
+      max_z: 50.0
+      negative: False
+    ```
+
+- The green points (topic name: `/localization/pose_estimator/points_aligned`)
+  represent the NDT localization aligned points on the map in the image below.
+  The default range is 60 meters, meaning points beyond this distance cannot be utilized.
+
+<figure markdown>
+  ![ytu-campus-pcd-range](images/ndt-range-60m.png){ align=center }
+  <figcaption>
+   NDT aligned points within a 60-meter crop box range
+  </figcaption>
+</figure>
+
+- If we wish to increase our NDT input point cloud range,
+  we can make the following changes in the `crop_box_filter_measurement_range.param.yaml` file.
+  However,
+  please bear in mind that since this alteration enlarges the size of the NDT input point cloud,
+  it will require additional resources on your processor.
+
+  ```diff
+  /**:
+    ros__parameters:
+      input_frame: "base_link"
+      output_frame: "base_link"
+  -   min_x: -60.0
+  +   min_x: -150.0
+  -   max_x: 60.0
+  +   max_x: 150.0
+  -   min_y: -60.0
+  +   min_y: -150.0
+  -   max_y: 60.0
+  +   max_y: 150.0
+      min_z: -30.0
+      max_z: 50.0
+      negative: False
+  ```
+
+<figure markdown>
+  ![ytu-campus-pcd-range](images/ndt-range-150m.png){ align=center }
+  <figcaption>
+    NDT aligned points within a 150-meter crop box range
+  </figcaption>
+</figure>
+
+### Voxel-grid filter for localization input
+
+- Voxel Grid filtering is a technique used in point cloud pre-processing
+  to reduce the density of 3D point cloud data while preserving its overall structure.
+  This is especially useful in scenarios
+  where high-resolution point clouds are computationally expensive
+  to process or unnecessary for the task at hand.
+  The default voxel size for all three axes in Autoware is 3.0.
+  If you have additional computational resources,
+  reducing the voxel size can enhance localization accuracy.
+  However, please be aware that this will demand more computational power.
+
+!!! note " The default [voxel_grid_filter.param.yaml](https://github.com/autowarefoundation/autoware_launch/blob/main/autoware_launch/config/localization/voxel_grid_filter.param.yaml) file for localization util."
+
+    ```yaml
+    /**:
+      ros__parameters:
+      voxel_size_x: 3.0
+      voxel_size_y: 3.0
+      voxel_size_z: 3.0
+    ```
+
+- The default voxel size for downsampling is 3.0,
+  and the resulting aligned points will resemble the image below.
+
+<figure markdown>
+  ![voxel-size-1.0](images/voxel-size-3.0.png){ align=center }
+  <figcaption>
+    Voxel size 3.0 aligned points (more sparse)
+  </figcaption>
+</figure>
+
+- We have sufficient computational power available on our tutorial vehicle,
+  so we will reduce the voxel size to improve localization accuracy.
+  Feel free to experiment with tuning the voxel size for your own computer setup.
+
+  ```diff
+
+  /**:
+    ros__parameters:
+  - voxel_size_x: 3.0
+  + voxel_size_x: 1.0
+  - voxel_size_y: 3.0
+  + voxel_size_y: 1.0
+  - voxel_size_z: 3.0
+  + voxel_size_z: 1.0
+  ```
+
+<figure markdown>
+  ![voxel-size-1.0](images/voxel-size-1.0.png){ align=center }
+  <figcaption>
+    Voxel size 1.0 aligned points (more dense but it requires computational power)
+  </figcaption>
+</figure>