Yara Khaluf1
and
Marco Dorigo2 (2015)
1Department of Computer Science, University of Paderborn, Germany
2IRIDIA, Université Libre de Bruxelles, Belgium
Table of Contents |
This supplementary material contains instructions to download the code to run the cleaning task experiment presented in the main paper (section 5) and explains how to compile and run it.
The ARGoS simulator can be downloaded here
The cleaning task code can be downloaded here
Open a shell, go to the directory where you unpacked the tar.bz2 file and type:
$ mkdir build
$ cd build
To produce fast but not debuggable code, type:
$ cmake -DCMAKE_BUILD_TYPE=Release ..
To produce slow but debuggable code, type:
$ cmake -DCMAKE_BUILD_TYPE=Debug ..
Launch the compilation with the command:
$ make
If you find no error, you are ready to go to the next phase.
Set the environment variable ARGOS PLUGIN PATH to the full path in
which the build/ directory is located:
$ export ARGOS_PLUGIN_PATH=/path/to/build/
To run a cleaning task experiment, the configuration files should be in the directory "experiments". Therefore, go to that directory and type:
$ argos3 -c cleaning_robots.argos
Note that the experiment stops when all the robots become inactive.
The experiment parameters, that the user can set in the experiment configuration file, are:
An experiments generates two output files. Both are located in the "experiments" directory:
In the sample video below, we present a swarm of 50 homogeneous foot-bots performing a cleaning task. The white traces indicate the surface cleaned by the robots while moving in the arena. When the robots have maintenance issues (e.g., their battery is low, they need to be repaired, …) they move to the maintenance area, i.e., the grey area on the right side of the arena. This happens with rate mu. Robots in the maintenance area get repaired at rate lambda (lambda < mu) and then re-join the cleaning tasks.
Robots set their LEDS to green while they are cleaning and to white while they are avoiding obstacles (other robots). When in the maintenance area, robots set their LEDs to red.
The speed of the video is eight times faster than the simulation time. In the code available for downloading, we have removed the visualization of the white traces that indicate the surface cleaned as it slows down the simulation dramatically.