Code Monkey home page Code Monkey logo

simcloud's Introduction

Simcloud

This repository contains packages and setup files to run ROS-based robot simulations. The simulation environment is set up and run using the provided docker image (that needs to be built before use).

List of environments/worlds:

Empty world Simple shapes world Fire station world
Coolsingel world Playground world Collapsed house

List of robots:

Rover UAV NXP Drone

Building the docker image:

If you are new to docker, have a look at the DOCKER_README.md file in the simcloud/docker folder to install docker and see how to build images.

To build the main simcloud image, run the following command from within the directory with the Dockerfile (simcloud/docker/ros_melodic_desktop_px4/):

docker build -t ros_melodic_desktop_px4 .

Running a demo drone simulation:

To run a demonstration of the simulation environment (drone in a fire station), follow the provided DEMO_README.md file in the demo directory.

Setting up the Simcloud environment:

  1. Move to the simcloud repository folder:

    cd simcloud
  2. Start your docker container from here using the provided script. Make sure to select the right script based on your machine's graphics card! (If it doesn't work you might need to build this docker image):

    ./docker/ros_melodic_desktop_px4/run.sh

    or

    ./docker/ros_melodic_desktop_px4/run_intel.sh

    Note: You can open multiple terminals running in the same docker container. To do this, from the host terminal run:

    docker exec -it ros_melodic_desktop_px4 /bin/bash

    (Remember to source the scripts below to set up required environment variables in this new terminal as well)

  3. Move into the projects folder to access the simcloud files from your host:

    cd /projects/
  4. Move into the ros_packages folder (this will be your ros workspace):

    cd ros_packages
  5. Run catkin_make

  6. Source the ROS environment: source devel/setup.bash

  7. (Optional) If you would like to work with drones, you need to setup the px4 autopilot software. To do this, source the init_uav_px4.sh script in the uav ROS package (to setup the correct variables):

    source $(rospack find uav)/scripts/init_uav_px4.sh
    # OR source src/uav/scripts/init_uav_px4.sh

    Note: If you source your ROS workspace's setup.bash file again, you need to re-source the init_uav_px4.sh script to setup the ROS_PACKAGE_PATH environment variable. Otherwise the setup.bash will overwrite the ROS_PACKAGE_PATH and your program will not find the px4 package.

Start the environment:

  • world with simple shapes:

     roslaunch environments simple_shapes.launch
  • playground world:

     roslaunch environments playground.launch
  • collapsed house world:

     roslaunch environments collapsed_house.launch
  • coolsingel world:

     roslaunch environments coolsingel.launch
  • collapsed fire station

     roslaunch environments fire_station.launch
  • parking garage

     roslaunch environments parking_garage.launch
  • roffa

     roslaunch environments roffa.launch

Spawn and move robots in an environment:

  • Spawn a rover (TODO: add parameters to spawn multiple robots):

     roslaunch rover_gazebo spawn_rover.launch

    Tele-operate the rover using the [IJKL,] keys:

     rosrun teleop_twist_keyboard teleop_twist_keyboard.py
  • Spawn an UAV in a certain configuration, currently available [iris_camera, iris_depth_camera, iris_front_camera, iris_lidar, iris_rplidar] (TODO: add parameters to spawn multiple robots):

     roslaunch uav spawn_uav.launch uav_model:=iris_camera

    Or spawn the NXP drone:

     roslaunch uav spawn_nxp.launch

    You can command the UAV (position control) using the scripts in pos_control. For example, in a new terminal, run:

     rosrun collapsed_house_pos_control FLYinCollapsedHouse.py

    Finally, you need to arm the drone for flying by running the corresponding mavros commands in another terminal:

     rosrun mavros mavsys mode -c OFFBOARD
     rosrun mavros mavsafety arm
     # OR run `rosrun uav arm_uav.sh`
  • UAV's with different sensors are available:

    • iris_camera holds a downward facing camera
    • iris_front_camera has a front facing camera
    • iris_rplidar has a 2D rplidar on top
    • iris_lidar has a 3D velodyne lidar on top
    • iris_lidar_camera has a 3D velodyne lidar on top and a front facing camera --> however the tf tree seems broken for the lidar.

    Add the name of these models as value for the uav_model argument, for example:

      roslaunch uav spawn_uav.launch uav_model:=iris_front_camera
    

Use QGroundControl

To start QGroundControl move its folder and start the run script:

cd /QGroundControl
./qgroundcontrol-start.sh

In QGroundControl you can arm the UAV using the buttons highlighted in red in the below image.

You can also create a mission plan and set waypoints for the drone to follow (highlighted in blue in the images).

Finally, upload and start the mission (highlighted in green in the images). The drone should launch its flight in Gazebo.

(TODO) Spawn robots in an environment using preconfigured launch files:

  1. Rover in the shapes environment:

  2. Rover in the playground:

  3. Rover in the collapsed house:

  4. Rover on the Coolsingel:

  5. UAV on the Coolsingel:

  6. Multiple UAVs and a rover in the collapsed house:

Future TODO:

- create new combined launch files for different scenarios
- use parameters to launch as many robots you want
- connect to a config file to set parameters
- create videos
- create cloud hosting
- MVP:
	- Scripts to launch scenarios (Open API/Scenario)		
	- Rover, drone navigation stacks
	- Cloud hosting
	- GUI (Qtcreator?)
	- Security and protected files
	- ROS training pdfs
	- Sensor menu card?

Cheatsheet to use docker:

If you have already installed docker then you can use the following lines to start docker and open new terminals. If you need to install it, please jump to the installation section.

  1. Move into the folder of the files you would like to use inside docker:

    cd ~/<path-to-your-ros-packages>/
  2. Start docker:

    ./<path-to-your-docker-image/run.sh 
  3. Inside the docker image move into the /projects folder to access the files from your host folder.

  4. Open a new terminal inside the docker environment:

    docker exec -it <name-of-your-docker-image> /bin/bash
  5. Source the environment variables in this terminal as well:

    . ros_entrypoint.sh
  6. Move into the projects folder to access files from your host:

    cd projects/
  7. Move into the ros_packages folder ( this will be your ros workspace):

    cd ros_packages
  8. Source the environment: source devel/setup.bash

Special thanks to the MASCOR Institute, FH Aachen University of Applied Sciences for their summer school and uav workshop! We have learned a lot from it and it provided an excellent base for creating this repository!

simcloud's People

Contributors

reka-berci-hajnovics avatar sjauhri avatar b00tss avatar 0l3-git avatar ludost avatar

Forkers

linecomparison

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.