ma_ws

Repository for MA RWTH. Compared with the original Repository, the main differences are:

1. Add hdl_map_update package.
2. Modifiy the globalmap_server_nodelet.cpp in the hdl_localization/apps to match the new algorithm.

Installation

1. cd ~
2. git clone https://github.com/YunongPan/ma_ws.git
3. cd ~/ma_ws
4. catkin_make

Rasterization

1. Put .pcd file of big point cloud map into /ma_ws/src/hdl_map_update/pcd_files
2. Modify original_file_pcd in /ma_ws/src/hdl_map_update/pcd_files/pcd_splitter.py to match the name of large point cloud map.
3. Modify chunk_size.
4. cd ~/ma_ws/src/hdl_map_update/pcd_files
5. python pcd_splitter.py

Start map_update testing

1. Start testing with installing urbant_ws. Please see https://git.rwth-aachen.de/mobile-robotics/urbant/urbant_ws
2. Copy the ma_515.world file in /ma_ws/src/hdl_map_update/world into /urbant_ws/src/urbant_simulation/worlds
3. Modify the value of "world_name" in urbant_ws/src/urbant_simulation/launch/world/city.launch to "$(find urbant_simulation)/worlds/ma_515.world"
4. Open a terminal, cd ~/urbant_ws
5. roslaunch urbant_simulation start.launch gpu:=false gazebo_gui:=true gps_switch:=true lidar_switch:=true world:=city
6. Modify parameters in /ma_ws/src/hdl_localization/apps/globalmap_server_nodelet.cpp and /ma_ws/src/hdl_map_update/src/map_update.cpp
7. Open a terminal, cd ~/ma_ws
8. catkin_make
9. Open a terminal, cd ~/ma_ws
10. roslaunch hdl_localization hdl_localization_urbant.launch
11. Open a terminal,cd ~/ma_ws
12. roscd hdl_localization/rviz
13. rviz -d hdl_localization.rviz
14. Open a terminal,cd ~/ma_ws
15. roslaunch geonav_transform geonav_transform.launch
16. Open a terminal,cd ~/ma_ws
17. rosrun hdl_map_update map_update
18. Open a terminal,rosservice call /set_gps_pos
19. Open a terminal,rosrun teleop_twist_keyboard teleop_twist_keyboard.py to control robot.