A comparison of two methods for fusing information from a linear array of sonar sensors for obstacle localization
buir.contributor.author | Arıkan, Orhan | |
buir.contributor.orcid | Arıkan, Orhan|0000-0002-3698-8888 | |
dc.citation.epage | 541 | en_US |
dc.citation.spage | 536 | en_US |
dc.contributor.author | Arıkan, Orhan | en_US |
dc.contributor.author | Barshan, Billur | en_US |
dc.coverage.spatial | Pittsburgh, PA, USA | en_US |
dc.date.accessioned | 2016-02-08T12:01:09Z | |
dc.date.available | 2016-02-08T12:01:09Z | |
dc.date.issued | 1995 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.description | Date of Conference: 5-9 August 1995 | en_US |
dc.description | Conference Name: IEEE/RSJ International Conference on Intelligent Robots and Systems: Human Robot Interaction and Cooperative Robots, IEEE 1995 | en_US |
dc.description.abstract | The performance of a commonly employed linear array of sonar sensors is assessed for point-obstacle localization intended for robotics applications. Two different methods of combining time-of-flight information from the sensors are described to estimate the range and azimuth of the obstacle: pairwise estimate method and the maximum likelihood estimator. The variances of the methods are compared to the Cramer-Rao Lower Bound, and their biases are investigated. Simulation studies indicate that in estimating range, both methods perform comparably; in estimating azimuth, maximum likelihood estimate is superior at a cost of extra computation. The results are useful for target localization in mobile robotics. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T12:01:09Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 1995 | en |
dc.identifier.doi | 10.1109/IROS.1995.526268 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/27761 | |
dc.language.iso | English | en_US |
dc.publisher | IEEE | en_US |
dc.relation.isversionof | https://doi.org/10.1109/IROS.1995.526268 | en_US |
dc.source.title | Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems: Human Robot Interaction and Cooperative Robots, IEEE 1995 | en_US |
dc.subject | Collision avoidance | en_US |
dc.subject | Computational methods | en_US |
dc.subject | Computer simulation | en_US |
dc.subject | Mobile robots | en_US |
dc.subject | Motion control | en_US |
dc.subject | Parameter estimation | en_US |
dc.subject | Sensors | en_US |
dc.subject | Sonar | en_US |
dc.subject | Cramer-Rao lower bound method | en_US |
dc.subject | Maximum likelihood estimator | en_US |
dc.subject | Obstacle localization | en_US |
dc.subject | Pairwise estimate method | en_US |
dc.subject | Sonar sensors | en_US |
dc.subject | Sensor data fusion | en_US |
dc.title | A comparison of two methods for fusing information from a linear array of sonar sensors for obstacle localization | en_US |
dc.type | Conference Paper | en_US |
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