mav_control_rw

by ethz-asl

ethz-asl / mav_control_rw

Control strategies for rotary wing Micro Aerial Vehicles using ROS

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Control strategies for rotary wing Micro Aerial Vehicles (MAVs) using ROS

Overview

This repository contains controllers for rotary wing MAVs. Currently we support the following controllers: - mavlinearmpc : Linear MPC for MAV trajectory tracking - mavnonlinearmpc : Nonlinear MPC for MAV trajectory tracking - PIDattitudecontrol : low level PID attitude controller

Moreover, an external disturbance observer based on Kalman Filter is implemented to achieve offset-free tracking.

If you use any of these controllers within your research, please cite one of the following references

@incollection{kamelmpc2016,
                author      = "Mina Kamel and Thomas Stastny and Kostas Alexis and Roland Siegwart",
                title       = "Model Predictive Control for Trajectory Tracking of Unmanned Aerial Vehicles Using Robot Operating System",
                editor      = "Anis Koubaa",
                booktitle   = "Robot Operating System (ROS) The Complete Reference, Volume 2",
                publisher   = "Springer",
                year = “2017”,
}
@ARTICLE{2016arXiv161109240K,
          author = {{Kamel}, M. and {Burri}, M. and {Siegwart}, R.},
          title = "{Linear vs Nonlinear MPC for Trajectory Tracking Applied to Rotary Wing Micro Aerial Vehicles}",
          journal = {ArXiv e-prints},
          archivePrefix = "arXiv",
          eprint = {1611.09240},
          primaryClass = "cs.RO",
          keywords = {Computer Science - Robotics},
          year = 2016,
          month = nov
}

Installation instructions

To run the controller with RotorS simulator (https://github.com/ethz-asl/rotors_simulator), follow these instructions:

  • Install and initialize ROS indigo desktop full, additional ROS packages, catkin-tools:
  $ sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu `lsb_release -sc` main" > /etc/apt/sources.list.d/ros-latest.list'
  $ wget http://packages.ros.org/ros.key -O - | sudo apt-key add -
  $ sudo apt-get update
  $ sudo apt-get install ros-indigo-desktop-full ros-indigo-joy ros-indigo-octomap-ros python-wstool python-catkin-tools
  $ sudo rosdep init
  $ rosdep update
  $ source /opt/ros/indigo/setup.bash
  • Initialize catkin workspace:
    sh
    $ mkdir -p ~/catkin_ws/src
    $ cd ~/catkin_ws
    $ catkin config --cmake-args -DCMAKE_BUILD_TYPE=Release
    $ catkin init  # initialize your catkin workspace
    
  • Get the controllers and dependencies ```sh $ sudo apt-get install liblapacke-dev $ git clone https://github.com/catkin/catkinsimple.git $ git clone https://github.com/ethz-asl/rotorssimulator.git $ git clone https://github.com/ethz-asl/mavcomm.git $ git clone https://github.com/ethz-asl/eigencatkin.git

$ git clone https://github.com/ethz-asl/mavcontrolrw.git

* Build the workspace  
sh $ catkin build ```
  • Run the simulator and the linear MPC. In seperate terminals run the following commands
  $ roslaunch rotors_gazebo mav.launch mav_name:=firefly
  $ roslaunch mav_linear_mpc mav_linear_mpc_sim.launch mav_name:=firefly

You can use

rqt
to publish commands to the controller.

To run the controller with the multi sensor fusion (MSF) framewok (https://github.com/ethz-asl/ethzaslmsf): * Get msf ```sh $ git clone https://github.com/ethz-asl/ethzaslmsf.git ```

  • Run the simulator, the linear MPC and MSF, in seperate terminals run the following commands
  $ roslaunch rotors_gazebo mav.launch mav_name:=firefly
  $ roslaunch mav_linear_mpc mav_linear_mpc_sim_msf.launch mav_name:=firefly

Don't forget to initialize MSF.

Supported autopilots

Asctec Research Platforms

This control will work as is with the ros interface to the now discontinued Asctec research platforms (Hummingbird, Pelican, Firefly and Neo).

Pixhawk

This controller requires some small modifications to the PX4 firmware to allow yaw rate inputs. A modified version of the firmware can be found here. The firmware is interfaced with through a modified mavros node.

DJI

The controller can interface with DJI platforms through our mavdjiros_interface

Published and subscribed topics

The linear and nonlinear MPC controllers publish and subscribe to the following topics:

  • Published topics:

    • command/roll_pitch_yawrate_thrust
      of type
      mav_msgs/RollPitchYawrateThrust
      . This is the command to the low level controller. Angles are in
      rad
      and
      thrust
      is in
      N
      .
    • command/current_reference
      of type
      trajectory_msgs/MultiDOFJointTrajectory
      . This is the current reference.
    • state_machine/state_info
      of type
      std_msgs/String
      . This is the current state of the state machine of mavcontrolinterface.
    • predicted_state
      of type
      visualization_msgs/Marker
      . This is the predicted vehicle positions that can be used for visualization in
      rviz
      .
    • reference_trajectory
      of type
      visualization_msgs/Marker
      . This is the reference trajectory that can be used for visualization in
      rviz
      .
    • KF_observer/observer_state
      of type
      mav_disturbance_observer/ObserverState
      . This is the disturbance observer state used for debugging purposes. It includes estimated external forces and torques.
  • Subscribed topics:

    • command/pose
      of type
      geometry_msgs/PoseStamped
      . This is a reference set point.
    • command/trajectory
      of type
      trajectory_msgs/MultiDOFJointTrajectory
      . This is a desired trajectory reference that includes desired velocities and accelerations.
    • rc
      of type
      sensor_msgs/Joy
      . This is the remote control commands for teleoperation purposes. It also serves to abort mission anytime.
    • odometry
      of type
      nav_msgs/Odometry
      . This is the current state of the vehicle. The odometry msg includes pose and twist information.

The PID attitude controller publishes and subscribes to the following topics: - Published topics: -

command/motor_speed
of type

mav_msgs/Actuators
. This is the commanded motor speed.
  • Subscribed topics:
    • command/roll_pitch_yawrate_thrust
      of type
      mav_msgs/RollPitchYawrateThrust
      .
    • odometry
      of type
      nav_msgs/Odometry
      .

Parameters

A summary of the linear and nonlinear MPC parameters:

| Parameter | Description | | -------------------- |:-------------------------------------------------------------------------------:| |

use_rc_teleop
| enable RC teleoperation. Set to
false
in case of simulation. | |
reference_frame
| the name of the reference frame. | |
verbose
| controller prints on screen debugging information and computation time | |
mass
| vehicle mass | |
roll_time_constant
| time constant of roll first order model | |
pitch_time_constant
| time constant of pitch first order model | |
roll_gain
| gain of roll first order model | |
pitch_gain
| gain of pitch first order model | |
drag_coefficients
| drag on
x,y,z
axes | |
q_x, q_y, q_z
* | penalty on position error | |
q_vx, q_vy, q_vz
* | penalty on velocity error | |
q_roll, q_pitch
* | penalty on attitude state | |
r_roll, r_pitch, r_thtust
| penalty on control input | |
r_droll, r_dpitch, r_dthtust
| penalty on delta control input (only Linear MPC) | |
roll_max, pitch_max, yaw_rate_max
| limits of control input | |
thrust_min, thrust_max
| limit on thrust control input in
m/s^2
| |
K_yaw
* | yaw P loop gain | |
Ki_xy, Ki_z
* | integrator gains on
xy
and
z
axes respectively | |
position_error_integration_limit
| limit of position error integration | |
antiwindup_ball
| if the error is larger than this ball, no integral action is applied | |
enable_offset_free
* | use estimated disturbances to achieve offset free tracking | |
enable_integrator
* | use error integration to achieve offset free tracking | |
sampling_time
| the controller sampling time (must be equal to the rate of
odometry
message | |
prediction_sampling_time
| the prediction sampling time inside the controller |

* Through dynamic reconfigure, it is possible to change these parameters.


A summary of the PID attitude parameters:

| Parameter | Description | | -------------------- |:-------------------------------------------------------------------------------:| |

inertia
| vehicle inertia
3x3
matrix | |
allocation_matrix
| control allocation matrix depending on the configuration of the rotors | |
n_rotors
| number of rotors | |
rotor_force_constant
| force constant of the rotor in
N/rad^2
such that
F_i =rotor_force_constant*rotor_velocity^2
| |
rotor_moment_constant
| rotor moment constant such that
M = rotor_moment_constant*F_i
| |
arm_length
| distance between rotor and vehicle center | |
roll_gain, pitch_gain
* | error proportional term | |
p_gain, q_gain, r_gain
* | derivative gain | |
roll_int_gain, pitch_int_gain
*| integrator gains | |
max_integrator_error
| saturation on the integrator |

* Through dynamic reconfigure, it is possible to change these parameters.


References

[1] Model Predictive Control for Trajectory Tracking of Unmanned Aerial Vehicles Using Robot Operating System. Mina Kamel, Thomas Stastny, Kostas Alexis and Roland Siegwart. Robot Operating System (ROS) The Complete Reference Volume 2. Springer 2017 (to appear)

[2] Linear vs Nonlinear MPC for Trajectory Tracking Applied to Rotary Wing Micro Aerial Vehicles. Mina Kamel, Michael Burri and Roland Siegwart. arXiv:1611.09240


Contact

Mina Kamel fmina(at)ethz.ch

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