ME5413 Final Project

This work conducts the Mapping and Navigation of the robot in the Gazebo world Assemble Line, there are mainly 2 works conducted, which are shown below.

Mapping the environment by using the Jackal Robot.

Navigate the robot to the assembly line, packing area, and vehicle respectively.

Now it is going to introduce how to run every work :

Dependencies

System Requirements:

Ubuntu 20.04 (18.04 not yet tested)

ROS Noetic (Melodic not yet tested)

C++11 and above

CMake: 3.0.2 and above

Installation

This repo is a ros workspace, containing three rospkgs :

interactive_tools are customized tools to interact with the gazebo and your robot

jackal_description contains the modified jackal robot model descriptions

me5413_world the main pkg containing the gazebo world, and the launch files

dji_nav a navigation package using Dijkstra global planner and base local planner, which has the best performance

astar_nav are navigation package using A* global planner and base local planner.

avoid_nav a navigation package using the Dijkstra global planner and Teb local planner

my_nav navigation package is a package provided to new users who want to try their own method

calibrate_imu is a package used to calibrate the IMU sensor.

costmap_prohibition_layer are a package used to produce the prohibition layer in costmap.

master is a package used to provide Velodyne simulator.

Use the following command to download the repository : `

Clone your fork of this repo

git clone https://github.com/RoboSharkFall/ME5413_Final_Project.git
cd ME5413_Final_Project

Install all dependencies

rodeo install --from-paths src --ignore-src -r -y

Build

catkin_make

Source

source devel/setup.bash To properly load the gazebo world, you must have the necessary model files in the~/.gazebo/models/` directory.

There are two sources of models needed:

Gazebo Model `

Create the destination directory

cd mkdir -p .gazebo/models

Clone the official gazebo models repo (assuming home here `~/`)

git clone https://github.com/osrf/gazebo_models.git

Copy the models into the `~/.gazebo/models` directory

cp -r ~/gazebo_models/* ~/.gazebo/models `

Our customized models `

Install all dependencies

rosdep install --from-paths src --ignore-src -r -y

Build

catkin_make

Source

source devel/setup.bash `

Working Pipeline

0. Gazebo World This command will launch the gazebo with the project world :

# Launch Gazebo World together with our robot
roslaunch me5413_world world.launch

1. Manual Control If you wish to explore the gazebo world a bit, we provide you a way to manually control the robot around:

# Only launch the robot keyboard teleop control
roslaunch me5413_world manual.launch

Note: This robot keyboard teleop control is also included in all other launch files, so you don't need to launch this when you do mapping or navigation.

2. Mapping After launching Step 0, in the second terminal:

# Launch GMapping
roslaunch me5413_world mapping.launch

After finishing mapping, run the following command in the thrid terminal to save the map:

# Save the map as my_map in the maps/ folder
roscd me5413_world/maps/
rosrun map_server map_saver -f my_map map:=/map

You may want to use other mapping method, in this work we use other two method : A-LOAM and Fast-LIO, and the EVO tool is used for mapping performance evaluation. The repositories are as follows :

A-LOAM (https://github.com/nuslde/aloam_lidar_odom_result_generate)
Fast-LIO (https://github.com/hku-mars/FAST_LIO)
EVO tool (https://github.com/MichaelGrupp/evo)

The data you need for mapping and evaluation are as follows :

/mid/points : Topic publish the 3D lidar data.
/imu/data : Topic publish the IMU data.
/gazebo/ground_truth/state : Topic publish the ground truth data.

During running the mapping, run the following command to save the point cloud

rosrun pcl_ros pointcloud_to_pcd /input:=/globalmap

In order to do dowm sample and RANSAC to remove ground points, run the following python code :

pcd = o3d.io.read_point_cloud(pcl_file)
pcd_rotate = copy.deepcopy(pcd)
R = pcd_rotate.get_rotation_matrix_from_xyz(rotation=[0, 0, 5 * np.pi / 12])
pcd_rotate.rotate(R=R, center=np.array([0, 0, 0]))
o3d.visualization.draw_geometries([pcd, pcd_rotate])
downsample_pcd = pcd.voxel_down_sample(voxel_size=0.2)
o3d.visualization.draw_geometries([downsample_pcd])
o3d.io.write_point_cloud('path/for/saving/downsampled.pcd', downsample_pcd)
plane_model, inliers = pcd.segment_plane(distance_threshold=0.2, ransac_n=3, num_iterations=1000)
inlier_cloud = pcd.select_by_index(inliers)
outlier_cloud = pcd.select_by_index(inliers, invert=True)
if debug:
    print("Segmentation Time", time.time() - t)
    o3d.visualization.draw_geometries([outlier_pts])
o3d.io.write_point_cloud('path/for/saving/output.pcd', outlier_pts)

In order to turn the .pcd file to .pgm map and the yaml file for navigation, running the following command

mkdir -p ~/pcd2pgm_ws/src
cd ~/pcd2pgm_ws/src
catkin_init_workspace
git clone https://github.com/hujiax380/pcd2pgm.git
cd ~/pcd2pgm_ws

Then go to the /home/USERNAME/pcd2pgm_ws/src/pcd2pgm/pcd2pgm/src/test.cpp change the following code :

C++//Line 57
private_nh.param("file_directory", file_directory, std::string("/home/YOUR_USER_NAME/"));
//name of your device
ROS_INFO("*** file_directory = %s ***\n", file_directory.c_str());
private_nh.param("file_name", file_name, std::string("PCD_FILE_NAME"));
//Your pcd file name

After changing the code, run the following command :

catkin_make
source devel/setup.bash
rosrun pcd2pgm pcd2topic

then run the command rosrun map_server map_saver to save the map. Then change the map name to my_map.pgm and my_map.yaml, and modify code of my_map.yaml : image: map.pgm to image: my_map.pgm. After modify, copy the files to ME5413_Final_Project/src/me5413_world/maps/, the map is complete.

3. Navigation After install all the dependence and package, you can try to navigate the robot run the following command. we need to launch the gazebo model first to provide basic data and information:

# Launch the robot
cd ~/ME5413_Final_Project/
source devel/setup.bash
roslaunch me5413_world world.launch

Using 'dji_nav' package, which is Dijkstra global planner and base local planner(Recommened)

# Launch the dji_nav
source ~/ME5413_Final_Project/devel/setup.bash
roslaunch me5413_world dji_navigation.launch

using 'astar_nav' package, which using A* global planner and base local planner.

# Launch the astar_nav
source ~/ME5413_Final_Project/devel/setup.bash
roslaunch me5413_world atar_navigation.launch

using avoid_nav package, which using A* global planner and TEB local planner.

# Launch the avoid_nav
source ~/ME5413_Final_Project/devel/setup.bash
roslaunch me5413_world avoid_navigation.launch

RoboSharkFall/ME5413_Final_Project

ME5413 Final Project

Dependencies

Installation

Clone your fork of this repo

Install all dependencies

Build

Source

Create the destination directory

Clone the official gazebo models repo (assuming home here ~/)

Copy the models into the ~/.gazebo/models directory

Install all dependencies

Build

Source

Working Pipeline

Clone the official gazebo models repo (assuming home here `~/`)

Copy the models into the `~/.gazebo/models` directory