David Garzón Ramos and Mauro Birattari (creation date: November 2019; last update: June 2020)
Table of Contents
Research in swarm robotics has shown that automatic design is an effective approach to realize robot swarms. In automatic design methods, the collective behavior of a swarm is obtained by automatically configuring and fine-tuning the control software of individual robots. In this paper, we present TuttiFrutti: an automatic design method for robot swarms that belongs to AutoMoDe—a family of methods that produce control software by assembling preexisting software modules via optimization. The peculiarity of TuttiFrutti is that it designs control software for e-puck robots that can display and perceive colors using their RGB LEDs and omnidirectional camera. Studies with AutoMoDe have been so far restricted by the limited capabilities of the e-pucks. By enabling the use of colors, we significantly enlarge the variety of collective behaviors they can produce. We assess TuttiFrutti with swarms of e-pucks that perform missions in which they should react to colored light. Results show that TuttiFrutti designs collective behaviors in which the robots identify the colored light displayed in the environment and act accordingly. The control software designed by TuttiFrutti endowed the swarms of e-pucks with the ability to use color-based information for handling events, communicating, and navigating.
Below we show demonstrative videos of collective behaviors designed with TuttiFrutti, both in simulation and with physical robots. The videos show a swarm of 20 e-pucks performing three missions: STOP; AGGREGATION; and FORAGING. In the three missions, the walls of the arena provide to the robots relevant information in the form of color lights.
Alongside TuttiFrutti, we also show demonstrative videos of collective behaviors designed with EvoColor—a design method based on neuro-evolution
The complete set of 60 videos of the experimental runs we performed with physical robots, both for TuttiFrutti and EvoColor, is available to download here.
In STOP, the robots must stop moving as soon as signal of color green appears in the environment.
In AGGREGATION, the robots must aggregate in the black region where the color blue is displayed.
In FORAGING, the robots must forage in an environment that has two sources of items—the sources differ in the profit they provide and in the color displayed at their location. The blue source gives a profit of +1, and the green source gives a penalization of -1.
The control software produced by TuttiFrutti and EvoColor, and the code to automatically design collective behaviors with these methods is available to download here. Experimental results are available to download here.