Bio-inspired Active Vision for Obstacle Avoidance

Manuela Chessa, Saverio Murgia, Luca Nardelli, Silvio P. Sabatini, Fabio Solari


Reliable distance estimation of objects in a visual scene is essential for any artificial vision system designed to serve as the main sensing unit on robotic platforms. This paper describes a vision-centric framework for a mobile robot which makes use of bio-inspired techniques to solve visual tasks, in particular to estimate disparity. Such framework features robustness to noise, high speed in data processing, good performance in 3D reconstruction, the possibility to orientate the cameras independently and it requires no explicit estimation of the extrinsic parameters of the cameras. These features permit navigation with obstacle avoidance allowing active exploration of the scene. Furthermore, the modular design allows the integration of new modules with more advanced functionalities.


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Paper Citation

in Harvard Style

Chessa M., Murgia S., Nardelli L., P. Sabatini S. and Solari F. (2014). Bio-inspired Active Vision for Obstacle Avoidance . In Proceedings of the 9th International Conference on Computer Graphics Theory and Applications - Volume 1: WARV, (VISIGRAPP 2014) ISBN 978-989-758-002-4, pages 505-512. DOI: 10.5220/0004873705050512

in Bibtex Style

author={Manuela Chessa and Saverio Murgia and Luca Nardelli and Silvio P. Sabatini and Fabio Solari},
title={Bio-inspired Active Vision for Obstacle Avoidance},
booktitle={Proceedings of the 9th International Conference on Computer Graphics Theory and Applications - Volume 1: WARV, (VISIGRAPP 2014)},

in EndNote Style

JO - Proceedings of the 9th International Conference on Computer Graphics Theory and Applications - Volume 1: WARV, (VISIGRAPP 2014)
TI - Bio-inspired Active Vision for Obstacle Avoidance
SN - 978-989-758-002-4
AU - Chessa M.
AU - Murgia S.
AU - Nardelli L.
AU - P. Sabatini S.
AU - Solari F.
PY - 2014
SP - 505
EP - 512
DO - 10.5220/0004873705050512