Package tum_ardrone

This package contains the implementation corresponding to the following publications:

• Scale-Aware Navigation of a Low-Cost Quadrocopter with a Monocular Camera (J. Engel, J. Sturm, D. Cremers)
• Camera-Based Navigation of a Low-Cost Quadrocopter (J. Engel, J. Sturm, D. Cremers)
• Accurate Figure Flying with a Quadrocopter Using Onboard Visual and Inertial Sensing (J. Engel, J. Sturm, D. Cremers)

You can find a video on youtube. This Package builds on the well known monocular SLAM framework PTAM presented by Klein & Murray in their paper at ISMAR07. Please study the original PTAM website and the corresponding paper for more information on this part of the software. Also, be aware of the license that comes with it.

The code works for both the AR.Drone 1.0 and 2.0, the default-parameters however are optimized for the AR.Drone 2.0 by now.

Installation

with catkin

cd catkin_ws/src
git clone https://github.com/tum-vision/tum_ardrone.git -b hydro-devel
cd ..
rosdep install tum_ardrone
catkin_make

Quick start

Launch the nodes

roslaunch tum_ardrone ardrone_driver.launch
roslaunch tum_ardrone tum_ardrone.launch

Check status

On the GUI, under Drone Communication Status, you should see:

• Drone Navdata: XHz (X > 100)
• Pose Estimates: 33Hz

Keyboard control

• focus drone_gui window
• press ESC to activate KB control
• fly around with KB (see drone_gui for key assignments)

Joystick control

• rosrun joy joy_node
• press PS button on controller to activate it
• fly around (see drone_gui for key assignments)

Autopilot

• type command “autoInit 500 800” in top-left text-field
• click Clear and Send (maybe click Reset first) => drone will takeoff & init PTAM, then hold position.
• click on video to interactively set target (relative to current position); see drone_stateestimation => first fly up 1m and then down 1m to facilitate a good scale estimate, dont start e.g. by flying horizontally over uneven terrain (!).
• always have a finger on ESC or on the joystick for emergency-keyboard control :)

Nodes

drone_stateestimation

Estimates the drone’s position based on sent navdata, sent control commands and PTAM.

IMPORTANT: requires messages to be sent on both /ardrone/navdata (>100Hz) and /ardrone/image_raw (>10Hz), i.e. a connected drone with running ardrone_autonomy node, or a .bag replay of at least those two channels. ardrone_autonomy should be started with:

rosrun ardrone_autonomy ardrone_driver _navdata_demo:=0 _loop_rate:=500

#### Subscribed topics

• /ardrone/navdata
• /ardrone/image_raw
• /cmd_vel
• /tum_ardrone/com

Published topics

• /ardrone/predictedPose
• /tum_ardrone/com

Services

None

#### Parameters

• ~publishFreq: frequency, at which the drone’s estimated position is calculated & published. Default: 30Hz
• ~calibFile: camera calibration file. If not set, the defaults are used (camcalib/ardroneX_default.txt).
• UseControlGains: whether to use control gains for EKF prediction.
• UsePTAM: whether to use PTAM pose estimates as EKF update
• UseNavdata: whether to use Navdata information for EKF update

  UsePTAM and UseNavdata are set to false, the EKF is never updated and acts as a pure simulator, prediciting the pose based on the control commands received (on /cmd_vel). Nice for experimenting.

• PTAMMapLock: lock PTAM map (no more KF)
• PTAMSyncLock: lock PTAM map sync (fix scale and pose offsets etc.)
• PTAMMaxKF: maximum amount of KF PTAM takes.

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