Simultaneous localization and mapping: Difference between revisions

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}}</ref> which showed that solutions to SLAM exist in the infinite data limit. This finding motivates the search for algorithms which are computationally tractable and approximate the solution. The acronym SLAM was coined within the paper, "Localization of Autonomous Guided Vehicles" which first appeared in [[Information Systems Research|ISR]] in 1995.<ref>{{Cite journal|last1=Durrant-Whyte|first1=H.|last2=Bailey|first2=T.|date=June 2006|title=Simultaneous localization and mapping: part I|journal=IEEE Robotics Automation Magazine|volume=13|issue=2|pages=99–110|doi=10.1109/MRA.2006.1638022|s2cid=8061430|issn=1558-223X|doi-access=free}}</ref>

The self-driving STANLEY and JUNIOR cars, led by [[Sebastian Thrun]], won the DARPA Grand Challenge and came second in the DARPA Urban Challenge in the 2000s, and included SLAM systems, bringing SLAM to worldwide attention. Mass-market SLAM implementations can now be found in consumer robot vacuum cleaners.<ref>{{Cite news|last=Knight|first=Will|url=https://www.technologyreview.com/s/541326/the-roomba-now-sees-and-maps-a-home/|title=With a Roomba Capable of Navigation, iRobot Eyes Advanced Home Robots|work=MIT Technology Review|date=September 16, 2015|access-date=2018-04-25|language=en}}</ref> and [[Virtual reality headset|virtual reality headsets]] such as the [[Meta Quest 2]] and [[PICO 4]] for markerless inside-out tracking.

== See also ==