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We have decided to discontinue the publication of preprints on our preprint server as of 1 March 2024. The publication culture within mathematics has changed so much due to the rise of repositories such as ArXiV (www.arxiv.org) that we are encouraging all institute members to make their preprints available there. An institute's repository in its previous form is, therefore, unnecessary. The preprints published to date will remain available here, but we will not add any new preprints here.

MiS Preprint
19/2001

Evolving neural behaviour control for autonomous robots

Martin Hülse, Bruno Lara, Frank Pasemann and Ulrich Steinmetz

Abstract

An evolutionary algorithm for the creation of recurrent network structures is presented. The aim is to develop neural networks controlling the behaviour of miniature robots. Two different tasks are solved with this approach. For the first, the agents are required to move within an environment without colliding with obstacles. In the second task, the agents are required to move towards a light source. The evolution process is carried out in a simulated environment and individuals with high performance are also tested on a physical environment with the use of Khepera robots.

Received:
Apr 4, 2001
Published:
Apr 4, 2001

Related publications

inBook
2001 Repository Open Access
Martin Hülse, Bruno Lara, Frank Pasemann and Ulrich Steinmetz

Evolving neural behaviour control for autonomous robots

In: Artificial neural networks / G. Dorffner... (eds.)
Berlin : Springer, 2001. - pp. 957-962
(Lecture notes in computer science ; 2130)