LGMD based Neural Network for Automatic Collision Detection

Ana Silva, Jorge Silva, Cristina Santos

Abstract

Real-time collision detection in dynamic scenarios is a hard task if the algorithms used are based on conventional techniques of computer vision, since these are computationally complex and, consequently, time-consuming. On the other hand, bio-inspired visual sensors are suitable candidates for mobile robot navigation in unknown environments, due to their computational simplicity. The Lobula Giant Movement Detector (LGMD) neuron, located in the locust optic lobe, responds selectively to approaching objects. This neuron has been used to develop bio-inspired neural networks for collision avoidance. In this work, we propose a new LGMD model based on two previous models, in order to improve over them by incorporating other algorithms. To assess the real-time properties of the proposed model, it was applied to a real robot. Results shown that the LGMD neuron model can robustly support collision avoidance in complex visual scenarios.

References

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Paper Citation


in Bibtex Style

@conference{icinco12,
author={Ana Silva and Jorge Silva and Cristina Santos},
title={LGMD based Neural Network for Automatic Collision Detection},
booktitle={Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2012},
pages={132-140},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004044201320140},
isbn={978-989-8565-22-8},
}


in Harvard Style

Silva A., Silva J. and Santos C. (2012). LGMD based Neural Network for Automatic Collision Detection . In Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-8565-22-8, pages 132-140. DOI: 10.5220/0004044201320140


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - LGMD based Neural Network for Automatic Collision Detection
SN - 978-989-8565-22-8
AU - Silva A.
AU - Silva J.
AU - Santos C.
PY - 2012
SP - 132
EP - 140
DO - 10.5220/0004044201320140