Show Reference: "Auditory Robotic Tracking of Sound Sources Using Hybrid Cross-Correlation and Recurrent Networks"

Auditory Robotic Tracking of Sound Sources Using Hybrid Cross-Correlation and Recurrent Networks In Intelligent Robots and Systems, 2005. (IROS 2005). 2005 IEEE/RSJ International Conference on (August 2005), pp. 3554-3559, doi:10.1109/iros.2005.1545093 by John Murray, Stefan Wermter, Harry Erwin
@inproceedings{murray-et-al-2005,
abstract = {This paper describes an auditory robotic system capable of computing the angle of incidence of a sound source on the horizontal plane (azimuth). The system, with the use of an Elman type recurrent neural network ({RNN}), is able to dynamically track this sound source as it changes azimuthally within the environment. The {RNN} is used to enable fast tracking responses to the overall system over a set time, as opposed to waiting for the next sound position before moving. The system is first tested in a simulated environment and then these results are compared with testing on the robotic system. The results show that the development of a hybrid system incorporating cross-correlation and recurrent neural networks is an effective mechanism for the control of a robot that tracks sound sources azimuthally.},
author = {Murray, John and Wermter, Stefan and Erwin, Harry},
booktitle = {Intelligent Robots and Systems, 2005. (IROS 2005). 2005 IEEE/RSJ International Conference on},
citeulike-article-id = {9609970},
doi = {10.1109/iros.2005.1545093},
institution = {Hybrid Intelligent Systems, University of Sunderland, UK},
isbn = {0-7803-8912-3},
month = aug,
pages = {3554--3559},
posted-at = {2014-12-17 11:57:14},
priority = {2},
publisher = {IEEE},
title = {Auditory Robotic Tracking of Sound Sources Using Hybrid {Cross-Correlation} and Recurrent Networks},
url = {http://dx.doi.org/10.1109/iros.2005.1545093},
year = {2005}
}