Autonomous Mobile Robot

NUS Autonomous Mobile Robotics Final Project

Authors: Christina Lee, Dongen Li, Yuhang Han, and Shuo Sun
Project done by: Shen Xiaoting, Zeng Jinlin, Lei Haoran, Shang Jiajian

This repo implemented the gmapping slam algorithm, compare the DWA and TEB local planner, and Dijkstra and hybrid A* global planner for path planning

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
• This repo depends on the following standard ROS pkgs:
  • roscpp
  • rospy
  • rviz
  • std_msgs
  • nav_msgs
  • geometry_msgs
  • visualization_msgs
  • tf2
  • tf2_ros
  • tf2_geometry_msgs
  • pluginlib
  • map_server
  • gazebo_ros
  • jsk_rviz_plugins
  • jackal_gazebo
  • jackal_navigation
  • velodyne_simulator
  • teleop_twist_keyboard
  • ted_local_planner
• And this gazebo_model repositiory

Installation

This repo is a ros workspace, containing three rospkgs:

• interactive_tools are customized tools to interact with 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

Note: If you are working on this project, it is encouraged to fork this repository and work on your own fork!

After forking this repo to your own github:

# Clone your own fork of this repo (assuming home here `~/`)
cd
git clone https://github.com/<YOUR_GITHUB_USERNAME>/ME5413_Final_Project.git
cd ME5413_Final_Project

# Install all dependencies
rosdep install --from-paths src --ignore-src -r -y

# Build
catkin_make
# Source 
source devel/setup.bash

To properly load the gazebo world, you will need to have the necessary model files in the ~/.gazebo/models/ directory.

There are two sources of models needed:

• Gazebo official models

  # 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

  # Copy the customized models into the `~/.gazebo/models` directory
  cp -r ~/ME5413_Final_Project/src/me5413_world/models/* ~/.gazebo/models

Usage

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
# Gmapping
roslaunch me5413_world manual.launch
# Hector
roslaunch me5413_world mapping_hector.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

3. Navigation

Once completed Step 2 mapping and saved your map, quit the mapping process.

Then, in the second terminal:

# Load a map and launch AMCL localizer
# (1) Using DWA and Dijkstra
roslaunch me5413_world navigation.launch
# (2) Using TEB and Dijkstra
roslaunch me5413_world navigation_teb_loc.launch
# (3) Using DWA and hybrid A*
roslaunch me5413_world navigation_hybridastar.launch
# (4) Using TEB and hybrid A*
roslaunch me5413_world teb_hybridastar_nav.launch

Tasks

1. Map the environment

• You may use any SLAM algorithm you like, any type:
  • 2D LiDAR
  • 3D LiDAR
  • Vision
  • Multi-sensor
• Verify your SLAM accuracy by comparing your odometry with the published /gazebo/ground_truth/state topic (nav_msgs::Odometry), which contains the gournd truth odometry of the robot.
• You may want to use tools like EVO to quantitatively evaluate the performance of your SLAM algorithm.

2. Using your own map, navigate your robot

• From the starting point, move to the given pose within each area in sequence

  • Assembly Line 1, 2
  • Packaging Area 1, 2, 3, 4
  • Delivery Vehicle 1, 2, 3

• We have provided you a GUI in RVIZ that allows you to click and publish these given goal poses to the /move_base_simple/goal topic:

  

  Final routes (from assembly line 1 --> packaging area 1 --> delivery vehicle 2) of four methods in rviz:

  

• We also provides you four topics (and visualized in RVIZ) that computes the real-time pose error between your robot and the selelcted goal pose:

  • /me5413_world/absolute/heading_error (in degrees, wrt world frame, std_msgs::Float32)
  • /me5413_world/absolute/position_error (in meters, wrt world frame, std_msgs::Float32)
  • /me5413_world/relative/heading_error (in degrees, wrt map frame, std_msgs::Float32)
  • /me5413_world/relative/position_error (in meters wrt map frame, std_msgs::Float32)

• Visualization https://www.bilibili.com/video/BV12M4y1871D/?spm_id_from=333.1007.top_right_bar_window_history.content.click&vd_source=ffd190c162029c6edfcf1cd4805a65e3

Contribution

You are welcome contributing to this repo by opening a pull-request

We are following:

• Google C++ Style Guide,
• C++ Core Guidelines,
• ROS C++ Style Guide

License

The ME5413_Final_Project is released under the MIT License