Minimalistic approach to 3D obstacle avoidance behavior from simulated evolution

Titus R. Neumann, Susanne A. Huber, Heinrich H. Bülthoff

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

We present a minimalistic approach to establish obstacle avoidance and course stabilization behavior of a simulated flying autonomous agent in a 3D virtual world. The agent uses visual cues, and its sensory and motor components arc based on biological principles found in flies. A simple neural network is used for coupling the receptor and effector systems of the agent. In order to achieve appropriate reactions to sensory input, the connection weights are adjusted by a genetic algorithm under a closed loop action-perception condition.

Original languageEnglish
Title of host publicationArtificial Neural Networks - ICANN 1997 - 7th International Conference, Proceeedings
EditorsWulfram Gerstner, Alain Germond, Martin Hasler, Jean-Daniel Nicoud
PublisherSpringer Verlag
Pages715-720
Number of pages6
ISBN (Print)3540636315, 9783540636311
DOIs
Publication statusPublished - 1997
Event7th International Conference on Artificial Neural Networks, ICANN 1997 - Lausanne, Switzerland
Duration: 1997 Oct 81997 Oct 10

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1327
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Conference on Artificial Neural Networks, ICANN 1997
Country/TerritorySwitzerland
CityLausanne
Period97/10/897/10/10

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1997.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint

Dive into the research topics of 'Minimalistic approach to 3D obstacle avoidance behavior from simulated evolution'. Together they form a unique fingerprint.

Cite this