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Rick Ruijsink

dblp:194/2232 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1

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 · 44% 3D vision · 44% Legged, aerial and field robots · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping
obstacle avoidance
0.112012
The Appearance Variation Cue for Obstacle Avoidance · IEEE Trans. Robotics 2012
Computer vision › 3D vision › motion estimation
optical flow
0.112012
The Appearance Variation Cue for Obstacle Avoidance · IEEE Trans. Robotics 2012
Robotics › Legged, aerial and field robots › aerial robots › flapping-wing robot
flapping-wing micro air vehicle
0.012012
The Appearance Variation Cue for Obstacle Avoidance · IEEE Trans. Robotics 2012

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

optic flow · 0.1appearance variation cue · 0.1
YearPublicationVenuePosition
2012 The Appearance Variation Cue for Obstacle Avoidance
abstract
The appearance variation cue captures the variation in texture in a single image. Its use for obstacle avoidance is based on the assumption that there is less such variation when the camera is close to an obstacle. For videos of approaching frontal obstacles, it is demonstrated that combining the cue with optic flow leads to better performance than using either cue alone. In addition, the cue is successfully used to control the 16-g flapping-wing micro air vehicle DelFly II.
Guido de Croon, E. de Weerdt, Christophe De Wagter, B. D. W. Remes, Rick Ruijsink
IEEE Trans. Robotics5