Spatial cognition for robots: robot navigation from biological inspiration

Wyeth, Gordon and Milford, Michael (2009) Spatial cognition for robots: robot navigation from biological inspiration. IEEE Robotics and Automation Magazine, 16 3: 24-32. doi:10.1109/MRA.2009.933620

Author Wyeth, Gordon
Milford, Michael
Title Spatial cognition for robots: robot navigation from biological inspiration
Journal name IEEE Robotics and Automation Magazine   Check publisher's open access policy
ISSN 1070-9932
Publication date 2009-09-01
Year available 1997
Sub-type Article (original research)
DOI 10.1109/MRA.2009.933620
Open Access Status Not yet assessed
Volume 16
Issue 3
Start page 24
End page 32
Total pages 9
Place of publication Piscataway, NJ, United States
Publisher Institute of Electrical and Electronics Engineers
Language eng
Abstract The paper discusses robot navigation from biological inspiration. The authors sought to build a model of the rodent brain that is suitable for practical robot navigation. The core model, dubbed RatSLAM, has been demonstrated to have exactly the same advantages described earlier: it can build, maintain, and use maps simultaneously over extended periods of time and can construct maps of large and complex areas from very weak geometric information. The work contrasts with other efforts to embody models of rat brains in robots. The article describes the key elements of the known biology of the rat brain in relation to navigation and how the RatSLAM model captures the ideas from biology in a fashion suitable for implementation on a robotic platform. The paper then outline RatSLAM's performance in two difficult robot navigation challenges, demonstrating how a cognitive robotics approach to navigation can produce results that rival other state of the art approaches in robotics.
Keyword Biologically inspired robots
Learning and adaptive systems
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Brain Institute Publications
School of Information Technology and Electrical Engineering Publications
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Citation counts: TR Web of Science Citation Count  Cited 29 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 37 times in Scopus Article | Citations
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