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.
| Original language | English |
|---|---|
| Title of host publication | 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2005 |
| Publisher | IEEE Computer Society |
| Pages | 3554-3559 |
| Number of pages | 6 |
| ISBN (Print) | 0780389123 |
| DOIs | |
| Publication status | Published - 5 Dec 2005 |
| Externally published | Yes |
| Event | 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems - Edmonton, Canada Duration: 2 Aug 2005 → 6 Aug 2005 https://ieeexplore.ieee.org/xpl/conhome/10375/proceeding |
Publication series
| Name | IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS |
|---|---|
| Publisher | IEEE |
| ISSN (Print) | 2153-0858 |
| ISSN (Electronic) | 2153-0866 |
Conference
| Conference | 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems |
|---|---|
| Abbreviated title | IROS 2005 |
| Country/Territory | Canada |
| City | Edmonton |
| Period | 2/08/05 → 6/08/05 |
| Internet address |