SES_Group_Repo

About:

Prerequisites:

1. ROS Melodic on Ubuntu 18.04 or ROS Kinetic on Ubuntu 16.04.
2. Python catkin-tools
3. OpenCV - Computer Vision library
4. Boost - C++ library

Set up

1. Create a ROS workspace

mkdir -p ~/catkin_ws/src
cd catkin_ws
catkin_init_workspace

2. Clone this repository in your ROS workspace recursively along with the submodules

cd ~/catkin_ws/src
git clone --recurse-submodules -j8 https://github.com/mihirk284/SES_Group_Repo

3. Build your packages

cd ~/catkin_ws
catkin build

Usage

1) Test the installation

Try launching a sample test launch file

roslaunch rotors_gazebo mav_hovering_example.launch 

You should see a drone hovering some distance above the ground in your Gazebo simulator.

2) YOLO Implementation

Launch your drone in a Gazebo environment

roslaunch rotors_gazebo mav_hovering_example.launch 

Visualise the camera feed in RViz

rosrun rviz rviz

Click on "Add" and add the camera topic, you'll see a camera feed of the environment in which the drone is. Launch the YOLO object detector.

roslaunch darknet_ros yolo_v3.launch 

Try placing some objects like the aeroplane, table, turtlebot in the Gazebo environment in front of the camera and you'll see YOLO detecting it with a bounding box around that object.

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Contributors:

1. Mihir Kulkarni
2. SriSreyas Sundaresan
3. Shivangi Gupta
4. Vishal Singh
5. Aditya Bidwai