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A ROS C++ pacakge for Swarm of 20 robots(TurtleBot3) to perform a search and rescue operation. Each robot navigates autonomously to a designated waypoint, searches for humans, if a human is detected, plans a path to the nearest fire exit, and then returns back to its home location.

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Project_Finder : Finding Individuals for Disaster and Emergency Response

A ROS C++ package for Swarm of 20 robots(TurtleBot3) to perform a search and rescue operation. Each robot navigates autonomously to designated waypoint, searches for human, if a human is detected, plans a path to nearest fire exit and then returns back to its home location.

License: MIT

Project contibutors

  1. Naitri Rajyaguru, Robotics Graduate Student at University of Maryland, College Park.
  2. Mayank Joshi, Robotics Graduate Student at University of Maryland, College Park.

Overview

Firefighters all over the world, put the safety of others before their own. But still they are not equipped with the latest tools and technology to combat the disastrous environment. By providing a better idea and map of the unknown environment, the firefighters can minimize the search time and can rescue or take necessary actions as quickly as possible to save human lives.Search and rescue robots are an upcoming type of robots that can work along with the firefighters and behave as the first responder to any situation. They would search for the desired target, rescue if possible or at least notify the location of the target to the team. We propose a search and rescue robot which could work in any indoor scenario. We would also like to incorporate Acme Robotics state-of-the-art human detection and tracking module which was developed by us last year. The human detection module would enhance the bot’s capability to search for humans in the environment because they are the desired target in most of the rescue operations. We plan to use move_base for navigation, onboard LiDAR for dynamic obstacle avoidance and the RGB camera for human detection. Together they would work as a search and rescue system. Testing and Simulation would be done on ROS and Gazebo with a single robot, which could be scaled to ‘N’ number of robots depending upon the environment size and other factors. image

Deliverables

  • Project: Project Finder is search and rescue robot for hazardous environment
  • Overview of prosposed work, including risks, mitigation, timeline
  • UML and activity diagrams
  • Developer-level documentation

Presentation

  • Project FINDER presentation can be found here

Video Presentation

  • Project FINDER presentation video here

Quad Chart

  • Project FINDER here

Dependencies with licenses

  • OpenCV 4.5.0 (covered under the open-source Apache 2 License)
  • ROS Noetic
  • Move_base
  • Gazebo
  • GTest

Development Process

Following the Agile Iterative Process for Development, we switch roles of driver and navigator. Product backlog, iteration backlog and worklog can be found here and Sprint planning with review notes can be found here

World

  • We created a custom gazebo world which could simulate the requirements for our project image
  • For the custom world, we also generated a binary occupancy grid, loaded in rviz image
  • Generated map can be found here

Static Code analysis

  • Cppcheck results can be found here
  • Cpplint results can be found here

Installation

Install Requirements

bash ros_requirements.bash
run requirements.sh

Clone git repository

cd finderbot_ws/src
git clone --recursive https://github.com/naitri/project_finder

Execution of code

cd ~/finderbot_ws/src
catkin_make
source devel/setup.bash

In terminal 1

source devel/setup.bash
roslaunch project_finder main.launch

In terminal 2

source devel/setup.bash
rosrun project_finder finder

Results

  • Command prompt output image

ROS Test

  • All the current 29 tests (gtest + rostest) for this projects are passing.
cd ~/finderbot_ws/src
catkin_make
catkin_make run_tests

image

About

A ROS C++ pacakge for Swarm of 20 robots(TurtleBot3) to perform a search and rescue operation. Each robot navigates autonomously to a designated waypoint, searches for humans, if a human is detected, plans a path to the nearest fire exit, and then returns back to its home location.

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  • C++ 89.8%
  • CMake 6.9%
  • Shell 3.3%