The rapid rise of e-commerce services in the last decade, and its forecast for the future, have proved that the need for delivery services will be increasing, which needs to be addressed by improving the delivery infrastructure. Developments in technology have now made it possible to provide an autonomous solution, which can revolutionize the industry by
creating an autonomous delivery network that can accomplish
this task without the need for human intervention.
In this project, we propose a fleet of autonomous delivery
robots, called Musky, that can provide transportation services
for various kinds of small to medium-sized goods(<10 lbs)
for short-range hauling(<5 Miles) using Multi Fleet GPS Waypoint Navigation.
This repository contains a multi-robot autonomous delivery framework, that works with husky robots from ClearPath robotics, in a simulation environment. The robots called "Musky" can be controlled via command line inputs, where they can be made to traverse to a preset location to pick up an order from a restaurant and will deliver it to a preset delivery location.
Quad Chart
Project Proposal
Activity Diagram
Class Diagram
- Generating a new world file, as localization is problematic in UMD world
- Generated map for the above world using Gmapping and used the same for localization
- Created new UML diagram to reflect the change in code structure
- Created Stub Classes and Test cases stubs for the new UML
- Created header and source files according to the stubs which passed the tests
- Created a command line interface for controlling the fleet
- Created a Graphical User Interface to communicate and control the robots
- Created and released the package for the fleet system
Gazebo: Spawning Fleet of Huskies in temporary Dock Station 
Rviz: Spawning Fleet of Huskies in temporary Dock Station 
UMD Campus Map Mckeldin Library 
- The streets do not have any traffic or traffic signals, hence the robot can navigate freely on the pedestrian paths, except for a few obstacles along the way.
- The obstacles present on the pedestrian paths are of dimensions such that they do not block the complete pathway and will allow the robot to maneuver around it.
- The paths are even and do not contain extreme slopes.
- Ubuntu 20.04 using Noetic
Programing language: C++
Build system: cmake
Testing Library: Google Test
Continuous Integration: GitHub Actions CI, Coverall
Other: ROS, Gazebo, RViz, Clearpath Husky
- husky_navigation package, which uses gmapping, move_base and frontier_exploration [BSD-3-Clause License].
- CLI11 package for parsing command line input [BSD-3-Clause License].
- Risk 1: Error in Path planning Algorithm due to unknown constraints which might lead to delay in delivery time or failed delivery. Mitigation: This can be mitigated by improving the path planning algorithm by feeding the planning data to supervised learning ML algorithms and training the path planner to predict obstacles/possible unknown constraints.
- Risk 2: Unexpected shutdown of ROS Master might lead to the shutdown of all the available agents/Robots. Mitigation: This risk can be mitigated by migrating the whole project to ROS2 or by integrating a ROS1 bridge with ROS2.
- Risk 3: One of the sensors required for path planning might malfunction leading to erratic behavior. Mitigation: If such a condition occurs, the robot will be made to override the autonomous navigation signals and a human operator will manually control the robot.
- Due to narrow pathways, the robots are unable to find paths as the cost map generated have high padding. This can be mitigated by using smaller robots or by generating different paths.
ROS Noetic is required to run the code, it's installation can be found at ROS Noetic installation
As kivy is used for the GUI, it needs to be installed as follow
pip install https://github.com/kivymd/KivyMD/archive/master.zip
To run the code, first open a terminal and download the repository
git clone https://github.com/sumedhreddy90/MusketeersDeliveryFramework.git
Then, add the downloaded repository into your ROS workspace's src folder (eg. catkin_ws/src)
After adding the repository, change the directory of the repository to the workspace repository
cd ~/catkin_ws
To build the changes use
catkin_make
To source the build files use
source devel/setup.bash
Launch files are provided that will spawn multiple robots in a gazebo environment and will simultaneously open rviz. To use the launch file, run the following command in the same terminal
roslaunch musky_nav multi_husky_delivery.launch
Wait for all the windows to open fully, which can be verified by checking the ROS_INFO message in the terminal where the above launch file was launched. It should display Recovery behavior will clear layer 'obstacles'
After getting the above message, open a new terminal and navigate to the ROS workspace, using
cd ~/catkin_ws
and source the build files
source devel/setup.bash
To run the ROS node that controls the muskies, run the following code
rosrun musky_nav musk_init __name:=node1 1
Where __name:=node1 is used to create the instance of the node with a specified name, and 1 specifies the robot ID. The general command line code would be
rosrun musky_nav musk_init __name:=<node name> <Robot ID>
After the above command, the terminal will display all the options available for navigation
Where do you want the robot to go?
1 = Musketeers_Base-Station : 1
2 = Musketeers_Base-Station : 2
3 = Musketeers_Base-Station : 3
4 = Musketeers_Base-Station : 4
5 = Chipotle
6 = Sub-way
7 = Taco-bell
8 = Panda Express
9 = Iribe
10 = Mckeldin Library
11 = J.M Patterson Hall
12 = Domain
Select one of the above mentioned options and the robot will plan the trajectory and will move accordingly
The bases are configured to cater to only the closes restaurants, hence, selection of the pickup location can be done as follows
The robots can also be controlled via a GUI as follows
rosrun musky_nav musketeers_gui.py
To run the tests, run the following command from the workspace directory
rostest musky_nav ros_test.launch
Result for it would be
... logging to /home/starfleeet-robotics/.ros/log/rostest-starfleeet-25046.log
[ROSUNIT] Outputting test results to /home/starfleeet-robotics/.ros/test_results/musky_nav/rostest-test_ros_test.xml
[ INFO] [1639456426.976681234]: Waiting for the move_base action server to come up
[ INFO] [1639456431.979700155]: Waiting for the move_base action server to come up
[ INFO] [1639456436.979872319]: Waiting for the move_base action server to come up
[ INFO] [1639456441.980030316]: Waiting for the move_base action server to come up
[ INFO] [1639456446.980227198]: Waiting for the move_base action server to come up
[Testcase: testmusketeersTests] ... ok
[ROSTEST]-----------------------------------------------------------------------
[musky_nav.rosunit-musketeersTests/muskNavTest][passed]
[musky_nav.rosunit-musketeersTests/CommandVelTest][passed]
[musky_nav.rosunit-musketeersTests/concatTest][passed]
[musky_nav.rosunit-musketeersTests/master_test][passed]
SUMMARY
* RESULT: SUCCESS
* TESTS: 4
* ERRORS: 0
* FAILURES: 0