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16/01/2019 1:22am
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[Tutorials]

V-REP, Gazebo or ARGoS? A robot simulators comparison

Robots Multi-agent systems C++ AI Tutorials Date: 17/01/2018 :: 17 comments

Let’s have a look at three commonly used open-source simulators for robotics: V-REP, Gazebo and ARGoS, to find out which one suits your project the best.

How to compile code for e-puck robots on your computer

Tutorials Robots Multi-agent systems C++ Date: 31/03/2017 :: 2 comments

Compiling code natively on e-puck robots or cross-compiling on your computer can be very tedious. Luckily, there is a third option: compiling code on a virtualised robot system on your computer, then sending the program onto the robot.

Getting Started with Creeper

Tutorials Multi-agent systems Libraries Java Games AI Date: 27/05/2013

This tutorial helps you to create your own Java project with Creeper. As an alternative solution, you could simply download Creeper with the Demo project and rewrite class and package names within net.lenkaspace.creeper.demo to suit your own needs.

Developing in NXC using XCode

Lego Mindstorms Tutorials Date: 02/01/2012 :: 26 comments

After comparing a number of options, I chose NXC as a pretty good alternative to Robot-C. It supports a lot of things like sensor and motor management, playing of sounds, basic 2D and 3D graphics, etc. Most importantly, you can compile your programs from the command line or from XCode. This tutorial assumes knowledge of XCode 4 and of C. The NXC programming guide is a good reference.

Setting up NXC Development on a Mac

Lego Mindstorms Tutorials Date: 01/01/2012 :: 6 comments

This tutorial provides a step-by-step guide for setting up your Mac or Linux machine and your NXT brick for development with NXC. We will use the enhanced NXC firmware in order to enable extended functions for development.

Basic Matrix Operations in MATLAB

Tutorials Matlab Date: 13/11/2011

Here I provide a quick look up of commonly used matrix functions in MATLAB. All of these are compatible with Octave as well.

pyCreeper

The main purpose of pyCreeper is to wrap tens of lines of python code, required to produce graphs that look good for a publication, into functions. It takes away your need to understand various quirks of matplotlib and gives you back ready-to-use and well-documented code.

Novelty detection with robots using the Grow-When-Required Neural Network

The Grow-When-Required Neural Network implementation in simulated robot experiments using the ARGoS robot simulator.

Fast Data Analysis Using C++ and Python

C++ code that processes data and makes it available to Python, significantly improving the execution speed.

Designing Robot Swarms

This project looks at the challenges involved in modeling, understanding and designing of multi-robot systems.

Robustness in Foraging E-puck Swarms Through Recruitment

Swarms of five e-puck robots are used in a semi-virtual environment, facilitated by the VICON positioning system. Recruitment can make swarms more robust to noise in robot global positioning data.