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Sami Aitya

dblp:230/7026 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1991
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot navigation and mapping · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping
localization
0.011991
Real-time vision-based robot localization · ICRA 1991
Robotics › Robot navigation and mapping › localization
vision-based localization
0.011991
Real-time vision-based robot localization · ICRA 1991
Robotics › Robot navigation and mapping
landmark matching
0.011991
Real-time vision-based robot localization · ICRA 1991
Robotics › Robot navigation and mapping
visual landmark recognition
0.011991
Real-time vision-based robot localization · ICRA 1991

Methods — techniques the papers use, named apart from their topics

geometric tolerance · 0.0correspondence matching · 0.0
YearPublicationVenuePosition
1991 Real-time vision-based robot localization
abstract
An algorithm for robot localization using visual landmarks is described. This algorithm determines both the correspondence between observed landmarks (in this case vertical edges in the environment) and a preloaded map, and the location of the robot from those correspondences. The primary advantages of this algorithm are its use of a single geometric tolerance to describe observation error, its ability to recognize ambiguous sets of correspondences, its ability to compute bounds on the error in localization, and its fast execution. The current version of the algorithm has been implemented and tested on a mobile robot system. In several hundred trials the algorithm has not failed, and computes location accurate to within a centimeter in less than half a second.>
Sami Aitya, Gregory D. Hager
ICRA1