Attentional mechanisms for lateral line sensing through spectral analysis

Otar Akanyeti*, Camilla Fiazza, Paolo Fiorini

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

3 Citations (SciVal)


For autonomy in underwater robotics it is essential to develop context-driven controllers, capable of leading from perception to action without human intervention. One of the key challenges in this area is to extract reliable information from noisy sensor signals in a fast and efficient manner. In this context, we present a novelty-detection mechanism for lateral line sensing; this mechanism is meant to highlight interesting stimuli and separate them from the background, by bringing into focus new frequencies appearing in the environment. The method is fast and computationally cheap; additionally, it paves the way for characterization and classification of detected novelties. We present a testing framework to explore how to integrate frequency-related, temporal and spatial information and we demonstrate the viability of this approach in a multiple dipole-source environment.

Original languageEnglish
Title of host publicationFrom Animals to Animats 11 - 11th International Conference on Simulation of Adaptive Behavior, SAB 2010, Proceedings
Number of pages11
Publication statusPublished - 19 Nov 2010
Externally publishedYes
Event11th International Conference on the Simulation of Adaptive Behavior, SAB 2010 - Paris-Clos Luce, France
Duration: 25 Aug 201028 Aug 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6226 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on the Simulation of Adaptive Behavior, SAB 2010
CityParis-Clos Luce
Period25 Aug 201028 Aug 2010


Dive into the research topics of 'Attentional mechanisms for lateral line sensing through spectral analysis'. Together they form a unique fingerprint.

Cite this