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This is an old revision of this page, as edited by Anuran (talk | contribs) at 23:55, 22 February 2013 (The SLAM problem is the problem of central importance to mobile robotics over the last decade. Why on earth wasn't it marked high priority?). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.
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I tried

I tried to insert a link to Andrew Blake, pioneer of probabilistic methods for vision and tracking, but discovered there already is another Andrew Blake in the entertainment industry. Someone should resolve this ambiguity... Probots

Note: While A Blake has researched probabilistic methods and some SLAM methods use heavily a probabilistic approach, I consider unsuitable to force the issue here since there is no direct link between A Blake and SLAM. Baring differences is like having Kalman in the list because Kalman filters are used in some SLAM systems. —Preceding unsigned comment added by 137.222.103.132 (talk) 17:25, 3 June 2008 (UTC)[reply]

I like the intent of this sentence:

SLAM has not yet been fully perfected, but it is starting to be employed in unmanned aerial 
vehicles, autonomous underwater vehicles, planetary rovers and newly emerging domestic robots.

but have doubts as to what arial and underwater vehicles use SLAM for. I thought this technique was only for mapping indoor environments. -- BAxelrod 13:44, 15 October 2005 (UTC)[reply]

SLAM is a general tehnique/framework for creating maps dynamically while navigating in unknown territories. It is not domain-limited, and is therefore ideally suited for applications like autonomous arial and underwater navigation in unknown territories. Computational complexity may, however, pose a problem in such embedded devices. --Fredrik Orderud 23:35, 19 October 2005 (UTC)[reply]