Join GitHub today
GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together.Sign up
Failed to load latest commit information.
==================== == == == ARGoS EXAMPLES == == == ==================== AUTHOR: Carlo Pinciroli <firstname.lastname@example.org> DATE: 22/03/2015 *** INTRODUCTION *** In this package you'll find some basic examples to start using ARGoS. To run an experiment with ARGoS, you need to define two things: 1. the robot controllers 2. the experiment configuration You find example controllers in the controllers/ directory. The experiment configuration files are located in the experiments/ directory. Currently, ARGoS supports the foot-bot (a.k.a. the marXbot), and the e-puck. More robots will come in the future. All the examples, for the time being, are implemented for the foot-bot. *** THE EXAMPLES *** DIFFUSION In this example experiment, a foot-bot performs obstacle avoidance while navigating in an small square environment. The source files in controllers/footbot_diffusion/ contain all the basic information about how to write a robot controller. Follow the comments and you should grasp the first steps. The configuration files for this experiment are two: experiments/diffusion_1.argos and experiments/diffusion_10.argos. The first file places a single foot-bot in an obstacle-free environment. In this file all the basics about ARGoS configuration are covered. The second file is to see 10 robots in action. This files shows how to distribute objects (robots and obstacles) randomly in the environment without having to place them manually. SYNCHRONIZATION This example experiment reproduces the coupled oscillators of Mirollo and Strogatz. In the beginning, the robots flash their LEDs out of sync, but over time, seeing each other's LEDs, they synchronize. In this example you'll see how to use the camera, and how to distribute robots in a grid. FLOCKING This example experiment shows how to achieve foraging through the well known Lennard-Jones potential. The robots light up their central LED (called the beacon) in red. They use the omnidirectional camera to detect robots around and calculate the Lennard-Jones interaction force to all of them. The robots collectively go to a light source located in the origin. GRIPPING This examples shows how to use a cylinder as a movable object. Using a simple time-based logic, a foot-bot moves towards the cylinder, grips it, moves backwards dragging it, and finally releases it while keeping the backwards motion. FORAGING This example is a complete experiment. It shows how to interact with the simulation through the loop functions and the how to draw on the OpenGL graphical visualization through the Qt user functions. The arena is divided in two areas: a grey area that serves as nest, where the robots are initially deployed; and a white area where food items are scattered. The task of the foot-bots is to exit the nest, search for food items, grab them and bring them back to the nest. To simplify control, food items are just drawn as black spots on the ground, and when a robot passes over a food item it automatically grabs it. When a robot is transporting a food item, a cylinder is drawn on top of it. Each robot can transport only one item per time. Once a robot has grabbed an item, it must bring it back to the nest. The direction to/away from the nest is detectable through light sensors, that read the position of a set of lights displaced over the nest. EVOLUTION This example shows how to embed ARGoS into a genetic algorithm and how to evolve a simple neural network controller. In this example, a foot-bot is evolved to perform phototaxis. The example is composed of a neural network controller in the controllers/ directory, a loop function in the loop_functions/ directory and additional code in the embedding/galib directory to wrap ARGoS. The code is compiled only if the GALIB library is found. The library is searched for in /usr or /usr/local. If you installed the library in a different place, use the 'ccmake' command to set the correct path. You can download GALIB at http://lancet.mit.edu/ga/ or install it through your system's package manager. On Ubuntu type 'sudo apt-get install libga-dev', while on HomeBrew type 'brew install brewsci/science/galib'. *** COMPILATION *** In principle, you can compile your code however you want. In practice, the help of a build system makes your work much easier. In ARGoS, and in these examples, we use CMake. To compile the examples, open up a shell, go to the directory where you unpacked the tar.bz2 file and type: $ mkdir build $ cd build To produce debuggable code (slow), type: $ cmake -DCMAKE_BUILD_TYPE=Debug .. To produce fast but not debuggable code, type: $ cmake -DCMAKE_BUILD_TYPE=Release .. Finally, launch the compilation with the command: $ make If you find no error, you're ready to go to the next phase. *** TROUBLESHOOTING *** When you launch one of the two 'cmake' commands, you might get an error like 'package argos3_simulator' not found. This error has two possible causes: 1. You haven't installed ARGoS3 system-wide. To fix this, install ARGoS3 through the packages or with the command 'sudo make install' in the ARGoS3 build directory. 2. pkg-config can't find the file argos3_simulator.pc. When you install ARGoS3 from a package, this file is located in /usr/lib/pkgconfig/. When you install ARGoS3 from the sources, this file is located in $CMAKE_INSTALL_PREFIX/lib/pkgconfig/. If you don't set $CMAKE_INSTALL_PREFIX explicitly before compiling, by default it is set to /usr/local. If the file is present and pkg-config can't find it, add the directory where it's located to the environment variable PKG_CONFIG_PATH, e.g. $ export PKG_CONFIG_PATH=/usr/local/lib/pkgconfig/ *** RUNNING THE EXAMPLES *** To run an example, the configuration files have been written with the hypothesis that you run them in the directory where you unpacked the tar.bz2, NOT in the build/ directory. Therefore, go to that directory and type: $ argos3 -c experiments/diffusion_1.argos for the example obstacle avoidance with a single robot, $ argos3 -c experiments/diffusion_10.argos for the example obstacle avoidance with 10 robots, $ argos3 -c experiments/synchronization.argos for the synchronization experiment, $ argos3 -c experiments/flocking.argos for the flocking experiment, and $ argos3 -c experiments/foraging.argos for the foraging experiment. The evolution experiments are divided in two parts. The command $ build/embedding/galib/galib_phototaxis runs the evolution process with the GALib library. Then, the command $ argos3 -c experiments/galib-trial.argos allows one to test a specific neural network. The command $ build/embedding/mpga/mpga_phototaxis runs the multi-process genetic algorithm. Then, the command $ argos3 -c experiments/mpga-trial.argos allows one to test a specific neural network. *** WHAT'S NEXT? *** More examples and a complete manual. I'm in the process of writing it, I do it a little bit every day. If you have specific questions, you can contact me at <email@example.com>.