Evolution of Neuro-Controllers for Robots' Alignment using Local Communication

Alvaro Gutierrez, Elio Tuci, Alexandre Campo

Research output: Contribution to journalArticlepeer-review

11 Citations (SciVal)
114 Downloads (Pure)

Abstract

In this paper, we use artificial evolution to design homogeneous neural network controller for groups of robots required to align. Aligning refers to the process by which the robots managed to head towards a common arbitrary and autonomously chosen direction starting from initial randomly chosen orientations. The cooperative interactions among robots require local communications that are physically implemented using infrared signalling. We study the performance of the evolved controllers, both in simulation and in reality for different group sizes. In addition, we analyze the most successful communication strategy developed using artificial evolution.
Original languageEnglish
Pages (from-to)25-34
Number of pages10
JournalInternational Journal of Advanced Robotic Systems
Volume6
Issue number1
DOIs
Publication statusPublished - 01 Mar 2009

Fingerprint

Dive into the research topics of 'Evolution of Neuro-Controllers for Robots' Alignment using Local Communication'. Together they form a unique fingerprint.

Cite this