This repository adapts the ORB-SLAM library for pose estimation on the AR-Drone. Scale estimation for the monocular slam process is generated by comparing the ORB-SLAM pose estimate with the altitude estimate published in the /ardrone/navdata topic. There is also efficient collision checking functionality for the point cloud generated by ORB-SLAM.

The goal of this project is to provide an easy-to-use testbed for motion planning and control research using the AR-Drone

This is the driver for sending velocity commands from a computer to the AR-Drone and receiving sensor data via wifi connection. It is cloned from the git repo:

ARdrone driver repo

This is repo contains a simple keybord controller for manual flight. It is cloned from:

Keyboard drive repo

This is the SLAM library that is used for mapping and localization. It is cloned from the git repo:

Monocular slam repo

You will have to follow the setup and compilation instructions in the readme for this package carefully. This includes downlaod and installation of these dependencies:

• OpenCV. BSD license.

• Eigen3. For versions greater than 3.1.1 is MPL2, earlier versions are LGPLv3.

and probably some more dependent on your system.

This package is the adaptor for the ORB_SLAM2 library into the ROS catkin framework. The settings.yaml file in this package contains camera calibration parameters for the AR-Drone camera.

This package contains a collision detection function that organizes the ORB-SLAM point cloud into a kd-tree for efficient distance querries between the ardrone and obstacles detected by ORB-SLAM

Robot Operating System (ROS): ROS
Open Computer Vision (OpenCV): OpenCV
Eigen3: Eigen
Pangolin: Pangolin

1. You should create a local catkin workspace for the packages. Wherever you will have the top level directory run:

mkdir ardrone_ws
cd ardrone_ws
mkdir src
cd src 

2. Clone the project into /ardrone_ws/src/

cd ardrone_ws/src/

git clone [email protected]:idsc-frazzoli/ardrone_testbed.git

3. Compile ORB_SLAM2 (after installing its dependancies: Eigen3, OpenCV, Pangolin):

cd ardrone_ws/src/ORB_SLAM2
chmod +x build.sh
./build/sh

4. Initialize the catkin_workspace and compile the project:

cd /ardrone_ws/src/
catkin_init_workspace
cd /ardrone_ws/
catkin_make
source devel/setup.bash

5. Connect to the AR-DRone:

Plug in the AR-Drone and connect to it via Wifi from the computer you plan to run the project from.

6. Launch everything:

roslaunch main.launch

7. To fly the drone with the keyboard drive:

-Put the cursor over the QT gui that pops up for keyboard drive node

Emergency shutdown: Space Bar
Takeoff: Y
Land: H
Up: Q
Down: A
Turn Left: W
Turn Right: R
Move Left: S
Move Right: F
Forward: E
Backward: D

Scale estimation is based on vertical motion so in the first few seconds of flight, flying the AR-Drone vertically will lead to a good scale estimate.