Code upload for Dang's Student Project

README.md

@@ -71,3 +71,4 @@ To merge your changes/added files into the official match-ROS repository, we nee
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 | [250429](student_code/250429_real_time_stabilization/README.md) | Real-Time Compensation of Ground Irregularities for Mobile Robot in Construction Additive Manufacturing | Algorithm to stabilize the nozzle for additive manufacturing purposes using IMU-based inclination data during movement on uneven terrain |
+| [251127](student_code/251127_print_texture_localization/README.md) | Concept development for robot localization based on an object to be manufactured | Concept for texture-based localization approach for mobile manipulator based on the initial layers of the printed object, using image descriptors and ICP refinement|

student_code/251127_print_texture_localization/README.md

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+# Wall Localization Demo
+
+## Overview
+This folder contains the code developed for wall-based scanner localization using geometric and appearance-based matching. The approach localizes a vertical profiler or scanner relative to a known wall geometry by combining 2D image-based matching (LBP or SIFT) with 3D ICP refinement.
+
+**Author:** Linh Thach Dang  
+**E-Mail:** linh.thach.dang@stud.uni-hannover.de
+
+
+## Installation
+Copy this folder into the `src` directory of a catkin workspace and build it using `catkin_tools`.
+
+```bash
+cd ~/catkin_ws/src
+cp -r wall_localization_demo .
+cd ~/catkin_ws
+catkin build
+source devel/setup.bash
+```
+
+## Package
+### wall_localization_demo
+
+This package contains all nodes, scripts, and launch files required for:
+- offline wall map generation,
+- live localization,
+- evaluation against ground truth.
+
+
+## Scripts
+
+All core scripts are located in `src/wall_localization_demo/`.
+
+### main.py
+Runs the live localization pipeline.  
+Subscribes to a LaserScan topic, transforms scan points into the wall frame, builds a local patch image, performs 2D localization (SIFT or LBP), refines the pose using ICP, and publishes the estimated scanner pose as the TF frame `scanner_icp_refined`.
+
+### localization_core.py
+Implements the core localization algorithms used by `main.py`, including patch generation, descriptor extraction, database matching, ICP refinement, and pose estimation.
+
+### compare_poses.py
+Logs ground truth and estimated poses during localization.  
+Samples TF and writes two CSV files:
+- `groundtruth_poses.csv` (wall → vertical_profiler_link)
+- `estimated_poses.csv` (wall → scanner_icp_refined)
+
+### move_along_wall.py
+Moves the robot along the wall at a fixed offset to generate continuous scan data during experiments.
+
+### pcl2texture.py
+Utility script to convert point cloud data into image or texture representations of the wall.

student_code/251127_print_texture_localization/wall_localization_demo/.gitignore

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+rosbag
+.vscode
+.git
+
+*.csv
+*.png
+*.jpg
+*.obj
+*.dae
+*.npy
+*.npz
+*.pkl

student_code/251127_print_texture_localization/wall_localization_demo/CMakeLists.txt

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+cmake_minimum_required(VERSION 3.0.2)
+project(wall_localization_demo)
+
+## Python3 required
+set(CMAKE_CXX_STANDARD 14)
+set(PYTHON_EXECUTABLE /usr/bin/python3)
+
+find_package(catkin REQUIRED COMPONENTS
+  rospy
+  std_msgs
+  geometry_msgs
+  sensor_msgs
+  nav_msgs
+  tf2_ros
+  tf_conversions
+  pcl_ros
+  pcl_msgs
+  gazebo_ros
+)
+
+## OpenCV (used inside localization_2d.py and main.py)
+find_package(OpenCV REQUIRED)
+
+catkin_python_setup()
+
+## Open3D is a Python dependency, not C++.
+## sklearn/skimage/numpy also Python dependencies.
+
+catkin_package(
+  CATKIN_DEPENDS
+    rospy
+    std_msgs
+    sensor_msgs
+    geometry_msgs
+    nav_msgs
+    tf2_ros
+    tf_conversions
+    pcl_ros
+    pcl_msgs
+    gazebo_ros
+)
+
+#############
+## INSTALL ##
+#############
+
+## Install Python scripts so rosrun/roslaunch can find them
+catkin_install_python(
+  PROGRAMS
+    src/wall_localization_demo/main.py
+    src/wall_localization_demo/move_along_wall.py
+    src/wall_localization_demo/compare_poses.py
+  DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
+)
+
+## Install launch files
+install(DIRECTORY launch/
+  DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}/launch
+)
+
+## Install config files
+install(DIRECTORY config/
+  DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}/config
+)
+
+## Install models (for Gazebo)
+install(DIRECTORY models/
+  DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}/models
+)
+
+## Install worlds
+install(DIRECTORY worlds/
+  DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}/worlds
+)
+
+## Install URDF files
+install(DIRECTORY urdf/
+  DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}/urdf
+)
+
+## Install any data (optional)
+install(DIRECTORY data/
+  DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}/data
+)

student_code/251127_print_texture_localization/wall_localization_demo/README.md

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+# wall_localization_demo
+
+## Overview
+This package implements a wall-based localization approach for a vertical profiler using LaserScan data in ROS Noetic.  
+The scanner pose is estimated relative to a known wall geometry by combining 2D image-based feature matching (LBP or SIFT) with 3D ICP refinement.  
+The package supports offline wall map generation, live localization in Gazebo simulation, and quantitative evaluation against ground truth data.
+
+**Author:** Linh Thach Dang 
+**E-Mail:** linh.thach.dang@stud.uni-hannover.de
+
+## Usage
+To run the live localization experiment in Gazebo, launch:
+```bash
+roslaunch wall_localization_demo run_localization.launch
+```
+This starts the simulation, initializes the localization pipeline, publishes required static transforms, and records ground truth and estimated poses.
+
+
+## Config files
+
+- ```offline_map.yaml```  
+Contains file paths to the offline wall map, point cloud, and descriptor databases used during localization.
+
+- ```estimator_params.yaml```  
+Defines parameters for the live localization pipeline, including frame definitions, filtering limits, and ICP settings.
+
+- ```localization_params.yaml```  
+Contains parameters for the 2D feature matching stage, such as descriptor configuration and matching thresholds.
+
+
+## Launch files
+
+- ```run_localization.launch```  
+Runs the complete live localization pipeline in simulation.
+
+Argument list:  
+method (type: string, default: sift): Feature matching method used for localization (sift or lbp).  
+pointcloud_topic (type: string, default: /scan_cloud): LaserScan input topic.
+
+- ```build_offline_map.launch```  
+Builds the offline wall map and descriptor databases from recorded scan data.
+
+- ```run_mapping_recording.launch```  
+Records wall scan data while the robot moves along the wall.
+
+- ```spawn_world_and_robot.launch```  
+Spawns the Gazebo world, wall model, and robot equipped with the vertical profiler sensor.
+
+
+## Nodes
+
+```scanner_pose_estimator```  
+
+This node performs the live wall-based localization. It processes incoming LaserScan data, builds local wall patches, performs 2D image-based matching, refines the pose using ICP, and publishes the estimated scanner pose as a TF transform.
+
+
+## Subscribed Topics
+
+```scan_cloud``` (sensor_msgs/LaserScan)  
+Laser scan data acquired by the vertical profiler sensor.
+
+```odom``` (nav_msgs/Odometry)  
+Odometry data of the mobile robot.
+
+## Parameters
+```wall_frame``` (type: string, default: wall): Reference frame attached to the wall geometry.
+
+```scanner_frame``` (type: string, default: vertical_profiler_link): Frame of the vertical profiler sensor.
+
+```base_frame``` (type: string, default: base_link): Robot base frame used for odometry and TF lookups.
+
+```odom_topic``` (type: string, default: /odom): Odometry topic used for motion tracking.
+
+```s_min_live``` (type: float, default: -0.6): Minimum along-wall coordinate for live scan filtering.
+
+```s_max_live``` (type: float, default: 0.6): Maximum along-wall coordinate for live scan filtering.
+
+```z_min_live``` (type: float, default: 0.0): Minimum height for live scan filtering.
+
+```z_max_live``` (type: float, default: 2.0): Maximum height for live scan filtering.
+
+```live_img_w``` (type: int, default: 6): Width of the live patch image.
+
+```live_img_h``` (type: int, default: 11): Height of the live patch image.
+
+```icp_max_iter``` (type: int, default: 50): Maximum number of ICP iterations.
+
+```icp_max_dist``` (type: float, default: 0.0035): Maximum correspondence distance used during ICP refinement.
+
+```method``` (type: string, default: sift): Feature matching method used for 2D localization.
+
+```stride``` (type: int, default: 16): Step size used when sliding the query window over the offline wall map during 2D localization.
+
+```max_query_kps``` (type: int, default: 60): Maximum number of keypoints extracted from the live patch and used for feature matching.
+
+```patch_h``` (type: int, default: 100): Height of the image patch used for 2D feature extraction and matching.
+
+```patch_w``` (type: int, default: 100): Width of the image patch used for 2D feature extraction and matching.
+
+```lbp_radius``` (type: int, default: 2): Radius of the circular neighborhood used for LBP feature computation.
+
+```lbp_points``` (type: int, default: 16): Number of sampling points on the LBP circular neighborhood.
+
+```lbphf_keep``` (type: int, default: 24): Number of most significant LBP-HF histogram bins retained for matching.
+
+```coarse_topk``` (type: int, default: 10): Number of top candidate matches retained during coarse 2D localization.
+
+```sift_ratio``` (type: float, default: 0.7): Lowe’s ratio threshold used to filter ambiguous SIFT feature matches.
+
+```sift_pca_dim``` (type: int, default: 4): Dimensionality of SIFT descriptors after PCA compression.
+
+```scale_bins``` (type: int, default: 3): Number of scale bins used for multi-scale SIFT feature extraction.
+
+```flann_trees``` (type: int, default: 4): Number of KD-trees used by the FLANN-based SIFT matcher.
+
+```flann_checks``` (type: int, default: 60): Number of search checks performed by the FLANN matcher during feature matching.
+
+

student_code/251127_print_texture_localization/wall_localization_demo/config/estimator_params.yaml

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+wall_frame: "wall"
+scanner_frame: "vertical_profiler_link"
+base_frame: "base_link"
+
+s_min_live: -1.0
+s_max_live: 1.0
+z_min_live: 0.0
+z_max_live: 5.0
+
+live_patch_s_length: 0.20
+
+method: "lbp"
+
+icp_max_dist: 0.05
+icp_max_iter: 50
+
+live_img_h: 11     # matches PATCH_H
+live_img_w: 6     # matches PATCH_W

student_code/251127_print_texture_localization/wall_localization_demo/config/localization_params.yaml

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+# ============================================================
+#  LOCALIZATION_2D PARAMETERS (OVERWRITES DEFAULT CONSTANTS)
+# ============================================================
+
+loc2d:
+
+  # -------- General --------
+  stride: 16
+  max_query_kps: 60
+  patch_h: 100
+  patch_w: 100
+
+  # -------- LBP-HF --------
+  lbp_radius: 2
+  lbp_points: 16           
+  lbphf_keep: 24
+  coarse_topk: 10
+
+  # -------- SIFT --------
+  sift_ratio: 0.7
+  sift_pca_dim: 4
+  scale_bins: 3
+
+  # -------- FLANN (SIFT matcher) --------
+  flann_trees: 4
+  flann_checks: 60
+

student_code/251127_print_texture_localization/wall_localization_demo/config/offline_map.yaml

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+cloud: "$(find wall_localization_demo)/data/demo_points.csv"
+out_map: "offline_map.npy"
+out_points: "offline_points.npy"
+delta_s: 0.005
+delta_z: 0.005

student_code/251127_print_texture_localization/wall_localization_demo/launch/build_offline_map.launch

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+<launch>
+
+  <!-- Build mapping dictionary (u,v)->(gray, point_indices) -->
+  <node pkg="wall_localization_demo" type="pcl2texture.py"
+        name="build_texture_map" output="screen">
+    <param name="cloud"
+           value="$(find wall_localization_demo)/data/mapping_run/wall_points_gazebo.csv"/>
+    <param name="out-map"
+           value="$(find wall_localization_demo)/data/mapping_run/offline_map_gazebo.npy"/>
+    <param name="out-points"
+           value="$(find wall_localization_demo)/data/mapping_run/offline_points_gazebo.npy"/>
+    <param name="delta-s" value="0.005"/>
+    <param name="delta-z" value="0.005"/>
+  </node>
+
+</launch>