Fly visual system inspired artificial neural network for collision detection

Zhang, Zhuhong and Yue, Shigang and Zhang, Guopeng (2015) Fly visual system inspired artificial neural network for collision detection. Neurocomputing, 153 (4). pp. 221-234. ISSN 0925-2312

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Fly visual system inspired artificial neural network for collision detection

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Abstract

This work investigates one bio-inspired collision detection system based on fly visual neural structures, in which collision alarm is triggered if an approaching object in a direct collision course appears in the field of view of a camera or a robot, together with the relevant time region of collision. One such artificial system consists of one artificial fly visual neural network model and one collision detection mechanism. The former one is a computational model to capture membrane potentials produced by neurons. The latter one takes the outputs of the former one as its inputs, and executes three detection schemes: (i) identifying when a spike takes place through the membrane potentials and one threshold scheme; (ii) deciding the motion direction of a moving object by the Reichardt detector model; and (iii) sending collision alarms and collision regions. Experimentally, relying upon a series of video image sequences with different scenes, numerical results illustrated that the artificial system with some striking characteristics is a potentially alternative tool for collision detection.

Keywords:Fly visual neural systems, artificial neural network, Collision detection, Collision region, Reichardt correlator, bmjgoldcheck, NotOAChecked
Subjects:G Mathematical and Computer Sciences > G730 Neural Computing
Divisions:College of Science > School of Computer Science
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ID Code:17881
Deposited On:17 Jul 2015 08:45

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