Summary

This repository contains the flight controller, and the vision-based state estimator for a quadrotor subjected to complete failure of a single rotor. The program runs in a ROS environment.

Citing

If you use this work in an academic context, please cite the following RA-L publication:

S. Sun, G. Cioffi, C. de Visser and D. Scaramuzza, "Autonomous Quadrotor Flight despite Rotor Failure with Onboard Vision Sensors: Frames vs. Events," IEEE Robot. Autom. Lett. (RA-L). 2021. PDF, VIDEO

@ARTICLE{SunAutonomous2021,
  author={S. {Sun} and G. {Cioffi} and C. {de Visser} and D. {Scaramuzza}},
  journal={IEEE Robotics and Automation Letters}, 
  title={Autonomous Quadrotor Flight despite Rotor Failure with Onboard Vision Sensors: Frames vs. Events}, 
  year={2021},
  volume={6},
  number={2},
  pages={580-587},
  doi={10.1109/LRA.2020.3048875}}  

Structure

\vio_estimator

Vision-based pose estimator using a standard camera.

\ftc_estimator

Rotation-corrected Complementary Filter and Extended Kalman Filter providing full pose and velocity estimates for the fault-tolerant flight controller.

\ftc_ctrl

Fault-tolerant flight controller that generates thrust command of individual rotors, using a Nonlinear Dynamic Inversion approach.

Installation

This installation guide was tested with Ubuntu 18.04

Requirements:

• CMake >= 3.0
• ROS (>= Kinetic) (see installation guide).

You also need to install the following packages for Ceres Solver:

sudo apt install liblapack-dev libblas-dev

Create a ROS workspace

mkdir -p ~/catkin_ws/src && cd ~/catkin_ws
catkin init

Configure the ROS environment

catkin config --extend /opt/ros/melodic --cmake-args -DCMAKE_BUILD_TYPE=Release

Clone the repository and dependencies

cd src/
git clone https://github.com/uzh-rpg/fault_tolerant_control.git
vcs-import < fault_tolerant_control/dependencies.yaml

Build the workspace

cd ~/catkin_ws && catkin build

Arm64

If you run the program in arm64 architecture, please add

set(ENV{ARM_ARCHITECTURE} aarch64)

in /vio_estimator/common/ze_common/CMakeLists.txt and /vio_estimator/common/ze_cmake/cmake/modules/ze_setup.cmake

in /fast_neon package, use branch /test/aarch64-compilation by

git checkout /test/aarch64-compilation

Test the vision-based state estimator

You can test the vision-based state estimator by running this rosbag recorded from real-flights using a standard camera (mvBLuefox).

roslaunch ze_vio_ceres live_Bluefox.launch
rosbag play <directory_of_the_bag>/data_bluefox.bag

Simulation

You can test the flight controller in RotorS, a MAV gazebo simulator. First of all, please install Gazebo.

Then run the following launch file

roslaunch ftc_ctrl testSim.launch

The drone is ready to fly in the simulator. We provide some simple commands in the /scripts folder

roscd ftc_ctrl && cd scripts

To take off, please type

./start_rotors.sh hummingbird

Then you can switch one motor off by running the script

./stop_rotor.sh hummingbird

You may decide which rotor to be turned off in simulation.yaml.

To control the quadrotor to a way point, e.g., xyz = [1.0 2.0 3.0], use the script

./reference.sh 1.0 2.0 3.0 hummingbird

Real flight test

You may reproduce our experiments in real flights, if you have

• A mvBluefox camera and it's ROS driver.
• A Terarranger-One range sensor and it's ROS_driver.
• A quadrotor that you can control the thrust of each individual rotor.
• A Joystick.
• Safety nets ;)

To start the flight controller, please run

roslaunch ftc_ctrl test.launch

The controller will publish rotor thrust command in a rostopic

/control_command/rotor_thrust 

You can feed these command to your low-level motor controller.

Add the vision-based estimator into the loop

Once the drone starts hovering before one motor is switched off, you can start the state estimator by running the following launch files:

roslaunch ze_vio_ceres live_Bluefox.launch

The estimated state will be published in the ROS topic

/state_est

which is used by the flight controller.