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Georgia Anousaki

dblp:33/2589 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2004
—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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping › localization
dead reckoning
0.012004
A Dead-reckoning Scheme for Skid-steered Vehicles in Outdoor Environments · ICRA 2004
Robotics › Robot navigation and mapping
SLAM
0.012004
A Dead-reckoning Scheme for Skid-steered Vehicles in Outdoor Environments · ICRA 2004

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

odometry · 0.0kalman filter · 0.0inertial navigation · 0.0
YearPublicationVenuePosition
2004 A Dead-reckoning Scheme for Skid-steered Vehicles in Outdoor Environments
abstract
A dead-reckoning scheme appropriate for skid-steered mobile robots is introduced to serve in a wider scheme for simultaneous localization and map-building. It is based on internal sensors (inertial data and odometry) only. The information from an experimentally derived kinematic model and an onboard inertial navigation system (INS), after a necessary pre-filtering stage, is fused using a simple and fast modified Kalman filter. We verify our approach with large scale experiments in outdoors structured environments and variable terrains, following paths with steep turns and variable velocity.
Georgia Anousaki, Kostas J. Kyriakopoulos
ICRA1