Biologically inspired visual landmark processing for simultaneous localization and mapping
This paper illustrates a method for finding useful visual landmarks for performing simultaneous localization and mapping (SLAM). The method is based loosely on biological principles, using layers of filtering and pooling to create learned templates that correspond to different views of the environme...
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| creator | Prasser, D.P. Wyeth, G.F. Milford, M.J. |
| description | This paper illustrates a method for finding useful visual landmarks for performing simultaneous localization and mapping (SLAM). The method is based loosely on biological principles, using layers of filtering and pooling to create learned templates that correspond to different views of the environment. Rather than using a set of landmarks and reporting range and bearing to the landmark, this system maps views to poses. The challenge is to produce a system that produces the same view for small changes in robot pose, but provides different views for larger changes in pose. The method has been developed to interface with the RatSLAM system, a biologically inspired method of SLAM. The paper describes the method of learning and recalling visual landmarks in detail, and shows the performance of the visual system in real robot tests. |
| doi_str_mv | 10.1109/IROS.2004.1389439 |
| format | Conference Proceeding |
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The paper describes the method of learning and recalling visual landmarks in detail, and shows the performance of the visual system in real robot tests.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Cameras</subject><subject>Computer science; control theory; systems</subject><subject>Computer vision</subject><subject>Control theory. Systems</subject><subject>Exact sciences and technology</subject><subject>Histograms</subject><subject>Information technology</subject><subject>Layout</subject><subject>Machine vision</subject><subject>Mobile robots</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Robot vision systems</subject><subject>Robotics</subject><subject>Simultaneous localization and mapping</subject><subject>Visual system</subject><isbn>9780780384637</isbn><isbn>0780384636</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFkE9LxDAQxQMiKOt-APGSi8fWpEnT5qiLugsLC_65eFmmTbKMpk1pusL66Q1UcBiYw_u9x2MIueYs55zpu83L7jUvGJM5F7WWQp-Rpa5qllbUUonqgixj_GRphC4lV5fk4wGDDwdswfsTxT4OOFpDvzEewVMPvelg_KLDGFobI_YH6sJII3ZHP0FvwzFSH5IZf2DC0NNkoB0MQyKvyLkDH-3y7y7I-9Pj22qdbXfPm9X9NkNesCkTpqwaK3QhayWNcAC60q3WoKy1komi5A1vNAijoVBOVs6wyoFrJK-VKaRYkNs5d4CYmrgR-hbjfhgxVT_teZ0YqXjibmYOU_C_PH9K_AIieGBs</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>Prasser, D.P.</creator><creator>Wyeth, G.F.</creator><creator>Milford, M.J.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope><scope>IQODW</scope></search><sort><creationdate>2004</creationdate><title>Biologically inspired visual landmark processing for simultaneous localization and mapping</title><author>Prasser, D.P. ; Wyeth, G.F. ; Milford, M.J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i120t-3d57be3924864d3faa979c99a6eee403251b1b9a3d9a26f47fd07fafb4186d243</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Cameras</topic><topic>Computer science; control theory; systems</topic><topic>Computer vision</topic><topic>Control theory. Systems</topic><topic>Exact sciences and technology</topic><topic>Histograms</topic><topic>Information technology</topic><topic>Layout</topic><topic>Machine vision</topic><topic>Mobile robots</topic><topic>Pattern recognition. Digital image processing. 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No.04CH37566)</btitle><stitle>IROS</stitle><date>2004</date><risdate>2004</risdate><volume>1</volume><spage>730</spage><epage>735 vol.1</epage><pages>730-735 vol.1</pages><isbn>9780780384637</isbn><isbn>0780384636</isbn><abstract>This paper illustrates a method for finding useful visual landmarks for performing simultaneous localization and mapping (SLAM). The method is based loosely on biological principles, using layers of filtering and pooling to create learned templates that correspond to different views of the environment. Rather than using a set of landmarks and reporting range and bearing to the landmark, this system maps views to poses. The challenge is to produce a system that produces the same view for small changes in robot pose, but provides different views for larger changes in pose. The method has been developed to interface with the RatSLAM system, a biologically inspired method of SLAM. 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| identifier | ISBN: 9780780384637 |
| ispartof | 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566), 2004, Vol.1, p.730-735 vol.1 |
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| language | eng |
| recordid | cdi_ieee_primary_1389439 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Applied sciences Artificial intelligence Cameras Computer science control theory systems Computer vision Control theory. Systems Exact sciences and technology Histograms Information technology Layout Machine vision Mobile robots Pattern recognition. Digital image processing. Computational geometry Robot vision systems Robotics Simultaneous localization and mapping Visual system |
| title | Biologically inspired visual landmark processing for simultaneous localization and mapping |
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