In the autonomous referee project, commercially available AR Parrot Drone Elite Edition 2.0 is used for the refereeing issues. The built-in properties of the drone that given in the manufacturer’s website are listed below in Table 1. Note that only the useful properties are covered, the internal properties of the drone are excluded.
The drone is designed as a consumer product and it can be controlled via a mobile phone thanks to its free software (both for Android and iOS) and send high quality HD streaming videos to the mobile phone. The drone has a front camera whose capabilities are given in Table 1. It has its own built-in computer, controller, driver electronics etc. Since it is a consumer product, its design, body and controller are very robust. Therefore, in this project, the drone own structure, control electronics and software are decided to use for positioning of the drone. Apart from that, the controlling of a drone is complicated and is also out of scope of the project.
Experiments, Measurements, Modifications
As mentioned before, the drone has its own camera and this camera is used to catch images. The camera is placed in front of the drone. However for the refereeing, it should look to the bottom side. Therefore it will be disassembled and will be connected to a swivel to tilt down 90 degrees. This will create some change in the structures. When this change is finished, it will be added here.
Software Restrictions on Image Processing
Using a commercial and non-modifiable drone in this manner brings some difficulties. Since the source code of the drone is not open, it is very hard to reach some data on the drone including the images of the camera. The image processing will be achieved in MATLAB. However, taking snapshots from the drone camera directly using MATLAB is not possible with its built-in software. Therefore an indirect way is required and this causes some processing time. The best time obtained with the current capturing algorithm is 0.4 Hz using 360p standard resolution (640x360). Although the camera can capture images with higher resolution, processing will be achieved using this resolution to decrease the required processing time.
One of the most important properties of a vision system is the field of view (FOV) angle. The definition of the field of view angle can be seen in the figure. The captured images has a ratio of 16:9. Using this fact and after some measurements the achieved measurements showed that it is near to 70° view although given that the camera has 92° diagonal FOV. The achieved measurements and obtained results are summarized in Table 2 . Here corresponding distance per pixel is calculated in standard resolution (640x360).
The following properties have to be initialized to be able to use the drone. For the particular drone that is used during this project, these properties have the values indicated by <value>:
- SSID <ardrone2>
- Remote host <192.168.1.1>
- Local port <5556>
- Local port <5554>
- Timeout <1 ms>
- Input buffer size <500 bytes>
- Byte order <litte-endian>
Note that for all properties to initialize the UDP objects that are not mentioned here, MATLAB's default values are used.
After initializing the UDP objects, the Navdata stream must be initiated by following the steps in the picture below.
The topcam is a camera that is fixed above the playing field. This camera is used to estimate the location and orientation of the drone. This estimation is used as feedback for the drone to position itself to a desired location. The topcam can stream images with a framerate of 30 Hz to the laptop, but searching the image for the drone (i.e. image processing) might be slower. This is not a problem, since the positioning of the drone itself is far from perfect and not critical as well. As long as the target of interest (ball, players) is within the field of view of the drone, it is acceptable.