The goal of this project is to build a Home Service Robot in ROS (Robot Operating System). To achieve this goal, a Turtlebot is deployed in a previously unknown custom Gazebo World. The Turlebot will use SLAM algorithm to create a Map of the world, use the generated Occupancy Grid Map for Localization and Path Planning, to perform a Pick and Place action.
For any autonomous mobile robot the ability to map the environment, localize itself within the environment, and navigate through the environment is important. This project uses the Turtlebot Stack that provides all the basic drivers for running and using a TurtleBot with ROS. The Turtlebot is launched in a custom Gazebo World previously not known to the robot. The Turlebot uses GMapping Software Package which provides laser-based SLAM (Simultaneous Localization and Mapping) to create 2-D occupancy grid map. The localization of the Turtlebot is done by AMCL Package which uses Adaptive Monte Carlo Localization method; while the Path Planning is based on the Dijkstra's, a variant of the Uniform Cost Search algorithm, to plan our robot trajectory from start to goal position. The ROS navigation stack permits your robot to avoid any obstacle on its path by re-planning a new trajectory once your robot encounters them. Further, turtlebot_viz stack is used to support user side interactions with the Turtlebot, used for RViz simulation, and a virtual object (Marker) is added in Rviz to visualize Pick and Drop action.
├── add_markers # added virtual object node
│ ├── CMakeLists.txt
│ ├── include
│ │ └── add_markers
│ ├── package.xml
│ └── src
│ ├── add_markers.cpp
│ └── test_addmarkers.cpp
├── LICENSE
├── MISC # images
│ ├── gazebo-1.png
│ ├── Gazebo-2.png
│ ├── Home-service.gif
│ ├── localisation-1.png
│ ├── localization-2.png
│ ├── map.png
│ ├── navigation-1.png
│ ├── Pick-up-1.png
│ ├── pick-up-2.png
│ ├── SLAM-1.png
│ └── turtlebot-1.png
├── my_map # generated 2D-OGM
│ ├── my_map.pgm
│ └── my_map.yaml
├── pick_objects # pick an place object node
│ ├── CMakeLists.txt
│ ├── include
│ │ └── pick_objects
│ ├── package.xml
│ └── src
│ └── pick_object.cpp
├── README.md
├── scripts # contains shell script files
│ ├── add_markers.sh
│ ├── home_service.sh
│ ├── launch.sh
│ ├── pick_object.sh
│ ├── test_navigation.sh
│ └── test_slam.sh
├── turtlebot # keyboard_teleop.launch file
│ ├── turtlebot_teleop
│ ├── ...
├── turtlebot_interactions # view_navigation.launch file
│ ├── turtlebot_rviz_launchers
│ ├── ...
├── turtlebot_simulator # turtlebot_world.launch file
│ ├── turtlebot_gazebo # amcl_demo.launch file
│ ├── ... # gmapping_demo.launch file
This project required a custom built Gazebo world, and a Robot.
| Turtlebot | Gazebo World |
|---|---|
 |
 |
Created a 2D Occupancy Grid Map by manually teleoperating Turtlebot in the unknown environment.
| Before SLAM | After SLAM |
|---|---|
 |
 |
| Localized Robot in Environment | Navigating to Goal Autonomously |
|---|---|
 |
 |
| Particles around the Turtlebot showing localization | Turtlebot autonomously navigating through the environment |
Modeled a virtual object with markers in RViz. The virtual object is the one being picked and delivered by the robot.
| Pick-up Point | Drop-off Point |
|---|---|
 |
 |
Note: The object is shown as a Green Colored Square
The Turtlebot is successfully able to navigate autonomously to the pick-up point where a virtual object is placed and then, carry that object to another location, to eventually place the object there. The below GIF demonstrates the working of the HOME SERVICE ROBOT:
In general, the robot is able to successfully perform the actions. While implementing the SLAM, due to feature-poor environment Turtlebot was not able to correctly perform SLAM of the environment. So, to tackle this, I tweaked minimum score parameter in the urdf file to be able to perform SLAM.
I would like to try a custom robot design. The virtual world could also be easier to map if more features or objects can be added. I would also like to implement other algorithms to visualize the comparision.
- Clone repo to
/home/workspace/src. Then, compile the code:
cd /home/workspace/
catkin_make
source devel/setup.bash
Note: This repository already includes official ROS packages compatible with this repository: gmapping, turtlebot_teleop, turtlebot_rviz_launchers, and turtlebot_gazebo. Their dependencies must be installed to succesfully use this repository:
rosdep -i install gmapping -y
rosdep -i install turtlebot_teleop -y
rosdep -i install turtlebot_rviz_launchers -y
rosdep -i install turtlebot_gazebo -y
- There are two options, whether to start the
Home Service Robotapplication directly or check working of individual process
To directly launch the application follow the following steps:
cd /rse_p7_udacity/scripts
./home_service.sh
To test the individual working of all the processes involved in programming of Home Service Robot such as SLAM Navigation and Localization Add Markers Pick Objects , follow the following steps:
cd /scripts
./<process_name> .sh --- replace *process name* with the actual process ---